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Measuring, using and analyzing skin resistance in kohms

Measuring, using and analyzing skin resistance in kohms



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What are ballpark ranges of skin resistance in Kohms for average men and their significance (for example 500-1000s = stressed vs 1000+ = fairly relaxed)

What do various skin resistances in kohms say about a person's emotional or arousal state:

For example: Is a skin resistance of less than 0 possible and what what does that say about the person


Galvanic Skin Response

Despite the challenges, numerous HCI researchers have used physiological data to observe user interactions in ways that would not otherwise be possible. An examination of some of these studies indicates the common theme of using these techniques to record real-time observations of a task in progress, as opposed to subjective, posttest response.

A study of cognitive load and multimodal interfaces used three different traffic control interfaces with three different task complexity levels to investigate the possibility of using galvanic skin response (GSR) to measure cognitive load. Participants used gesture-based, speech-based, or multimodal (speech and gesture) interfaces to complete tasks. Initial analysis of data from five participants indicated that average response levels were lowest for the multimodal interface, followed by speech and then gesture interfaces. For all three interfaces, the total response increased with task complexity. This was interpreted as providing evidence for the utility of using GSR to indicate cognitive loads. Analysis of specific recordings found GSR peaks to be correlated with stressful or frustrating events, with responses decreasing over time. Peaks were also correlated with major events that were thought to be cognitively challenging, including reading instructions and competing tasks ( Shi et al., 2007 ).

Another study used both galvanic skin response (GSR) and blood-volume pressure (BVP) to measure user frustration in an explicit attempt to develop methods for using multiple sensing technologies. The experimental design involved a game with several puzzles. Participants were told that the experimenters were interested in how brightly colored graphics would influence physiological variables in an online game. Unbeknown to the participants, the game software was rigged to randomly introduce episodes of unresponsiveness. As participants were being timed and had been offered a reward if they had the fastest task completion times, these delays would presumably cause frustration. 1 BVP and GSR responses were used to develop models that could distinguish between frustrating and nonfrustrating states ( Scheirer et al., 2002 ).

Interaction with computer games is a natural topic for physiological data. As anyone who has played video games knows, players can become excited while driving race cars, hunting aliens, or playing basketball on the computer. However, the fast-paced nature of these games limits the applicability of many techniques. Intrusive data collection techniques, such as “think-aloud” descriptions, interfere with the game-playing experience and posttest questionnaires fail to recapture all of the nuances of the playing experience ( Mandryk and Inkpen, 2004 ).

One study used various physiological data sources—GSR, EKG, cardiovascular rate, respiration rate, and facial EMG—to measure responses to computer games played against a computer and against a friend. Starting from the premise that the physiological data would provide objective measures that would be correlated to players' subjective reports of experiences with video games, the researchers hypothesized that preferences and physiological responses would differ when comparing playing against a computer to playing against a friend. Specifically, they hypothesized that participants would prefer playing against friends, GSR and EMG values would be higher (due to increased competition), and that differences between GSR readings in the two conditions would correspond to subjective ratings ( Mandryk and Inkpen, 2004 ).

To test these hypotheses, they asked participants to play a hockey video game, against the computer and against a friend. Participants were recruited in pairs of friends, so each person knew their opponent. The hypotheses were generally confirmed: participants found playing against a friend to be more exciting, and most had higher GSR and facial EMG levels when playing with a friend. Cardiovascular and respiratory measures did not show any differences. Investigation of specific incidents also revealed differences—participants had a greater response to a fight when playing a friend. Examination of the relationship between GSR, fun, and frustration revealed a positive correlation with fun and a negative correlation with frustration ( Mandryk and Inkpen, 2004 ). The use of multiple coordinated sensors to measure frustration in game playing continues to be an active area of research, with more recent papers exploring topics such as the impact of system delays ( Taylor et al., 2015 ).

EEGs have been also used by HCI researchers to develop brain-computer interfaces that use measurable brain activity to control computers ( Millán, 2003 ). Machine-learning algorithms applied to EEG signals have been used to distinguish between different types of activity. Similar to the study of cooperative gaming described earlier ( Mandryk and Inkpen, 2004 ), one study found that EEG signals could be used to distinguish between resting states, solo game play, and playing against an expert player ( Lee and Tan, 2006 ). Other HCI applications involving EEG signals include identifying images of interest from a large set ( Mathan et al., 2006 ) and measurement of memory and cognitive load in a military command-and-control environment ( Berka et al., 2004 ).

Electromyography has been used to measure a variety of emotional responses to computer interfaces. One study of web surfing tasks found strong correlations between facial EMG measures of frustration and incorrectly completed tasks or home pages that required greater effort to navigate ( Hazlett, 2003 ). Similar studies used EMG to measure emotional responses to videos describing new software features, tension in using media-player software ( Hazlett and Benedek, 2006 ), and task difficulty or frustration in word processing ( Branco et al., 2005 ). An experiment involving boys playing racing games on the Microsoft Xbox established the validity of facial EMG for distinguishing between positive and negative events ( Hazlett, 2006 ). Combinations of multiple physiological measures, including EMG, have also been used to study emotional responses ( Mahlke et al., 2006 ).

A broad body of work has explored the use of body sensing in a variety of healthcare domains, including assessment of disability, rehabilitation, and in use by clinicians. Several of these applications have been discussed in this chapter for a more in-depth discussion, see “Body Tracking in Healthcare” in O'Hara et al. (2016) .


Interpretation of Skin Impedance Measurements

HUMAN skin presents a high impedance to alternating current of low frequency 1 . The impedance is greatly reduced if the surface layers of the skin are abraded 2 . When the frequency of the applied a.c. is raised above 10 c/s, the impedance falls the equivalent circuit is a polarization impedance in parallel with a resistance 3 . The impedance of rabbit or pig skin is less than that of human skin, and is also less dependent on frequency (Fig. 1).


Results

Tensile response of skin

We first established the tensile stress-strain response of skin with hydrated edge-notched specimens to demonstrate its dramatic resistance to tearing (Fig. 1a–d), which we relate to synergistic structural changes occurring in the dermis during straining. Our experiments show that a notch in the skin did not propagate or induce fracture, it simply opened and blunted (Fig. 1e). This response is distinct from that of bone and tooth dentin, which are also collagenous materials but with mineral crystals 28,29,30 , where a notch can initiate cracking and failure (Fig. 1f), and from natural rubber, where again a small cut can readily cause fracture. This experiment pertains to the opening of a tear at the edge of the skin. These experiments are done on hydrated specimens to reflect reality. However, the mechanical response is significantly altered by decreasing the water content, as described in the Supplementary Discussion. The corresponding behaviour of an internal tear (Fig. 1g–j), which is more likely encountered in surgery, illustrates how an initially straight cut gradually deforms along a trajectory idealized by an ellipse that decreases its major axis (2a) and increases its minor axis (2b) until inversion occurs, as has been demonstrated computationally at the nanometre scale 31,32 . This change in notch geometry, shown in Fig. 1k,l, acts to diminish the stress concentration at the tip, as the local stress at the notch tip, σtip, is related to the globally applied stress, σapp, by σtip=σapp (1+2a/b). When the minor axis is zero, the local stress is infinite as the minor axis 2b increases and the major axis 2a decreases, this stress decreases. We show how this extraordinary flaw tolerance of skin is related to the reorganization of the collagen at any region of stress concentration.

(ad) The sequence of events where rabbit skin, containing an edge notch or tear (of a length half the lateral specimen dimension), is strained under uniaxial tensile loading the notch does not propagate but progressively yawns open under tensile loading. (e) Schematic illustration of skin with a pre-crack under loading the crack does not propagate but instead blunts. (f) Corresponding schematic of bone (transverse orientation) with a notch under loading the crack (white line) often propagates in a zig-zag pattern with multiple crack deflections. (gj) The deformation of a central notch in skin loaded in tension. Distortion of a central notch as specimen of rabbit skin is extended uniaxially. There is no increase in the initial length of the cut. (k,l) The notch root radius increases with axial extension of the specimen, with a consequent decrease in stress concentration. This is enabled by local straightening and stretching of fibres and by interfibrillar sliding. Scale bar in (ad), (gj) is 10 mm.

Before testing, the collagen fibres show a disordered, curvy morphology (Fig. 2a). Each fibre has a diameter of 5–10 μm and contains hundreds of

50-nm diameter collagen fibrils (Fig. 2b). TEM of the collagen fibrils reveals their principal orientations: nearly parallel and nearly perpendicular to the plane of the foil (Fig. 2c), with a curved trajectory their d-spacing, measured at 55 nm (Fig. 2d), is lower than the actual value because the fibrils are inclined to the plane of observation. Under load, fibre straightening and reorientation occurs towards the direction of straining, as illustrated in Fig. 2g–j. After loading, the collagen fibrils are aligned parallel, straightened and separated on the notched side, but relaxed from straightening and delamination on the unnotched side (Fig. 2e,f). SEM images demonstrate that the collagen fibres straighten and reorient leading to their separation into fibrils from the action of the interfibrillar shear and tensile stresses (shown later).

(a) Disordered arrangement of curved collagen fibres (SEM). (b) High magnification of a, collagen fibrils (

50 nm diameter) comprising each fibre (

1–10 μm diameter SEM). (c,d) Collagen fibrils in section plane parallel to skin surface including detail of sectioned fibrils (inset in c) and wavy structure (TEM). (e) Collagen fibrils at notched side are delaminated, aligning close to the tension direction after loading. The loading direction is shown by the arrow, (f) collagen fibrils at unnotched side are delaminated/relaxed after loading/unloading. (gj) Schematic of mechanisms of fibril deformation and failure under tension: (g) original configuration (h,i) straightening and reorientation of fibres with projected length in tensile direction increasing from L0 to L1, and L2 (j) separation into fibrils elastic stretching through the increase in collagen d spacing from d0 to d3, and sliding (schematically shown by S), increasing length in tensile direction to L3. R0R2 are the radii of curvature of collagen during stretching. Scale bars in af and the picture inset in c are 50 μm, 500 nm, 500 nm, 500 nm, 1 μm, 2 μm and 200 nm, respectively.

Mechanisms of deformation

The sequence of events can be analysed in terms of four mechanisms (Fig. 2g–j). One fibre with a reduced number of fibrils is used to schematically represent the process of deformation (Fig. 2g). The fibre stretches and reorients itself, increasing its projected length in the tensile direction from L0 to L1 and L2 (Fig. 2g–i). This takes place by increasing the radius of curvature of the initially curved fibres from R0 to R1 and R2 due to stretching, the angle with the tensile axis decreases from α0 to α1, and α2 (Fig. 2g–i). As the fibres are straightened, shear strains develop between the fibrils because of kinematic requirements. At a critical juncture, the shear stresses at the interfaces exceed the interfacial cohesive strength and the separation of fibrils ensues, leading to the last stage of deformation in which extensive interfibrillar displacement occurs (Fig. 2j). The displacement between two adjacent fibrils is indicated as S and the length along the tensile direction is now L3 (Fig. 2j). By the end of deformation, the d-spacing of collagen has increased from d0 to d3, as shown in Fig. 2g–j. Separation of the fibres into fibrils is shown in Fig. 2j.

Figure 3a shows the stress-strain curves of unnotched rabbit skin at two different strain rates, differing by a factor of 100: 10 −1 and 10 −3 s −1 . The plots represent a number of experiments (up to eight tests conducted for each condition) and the bands reflect the variation among individual results. The principal effect of increasing the strain rate is to increase the maximum stress, consistent with previous findings 6,7 , which we relate to the viscous effects of the extracellular matrix, including the sliding of collagen fibrils. Two orientations were tested: parallel and perpendicular to the backbone of the rabbit, which are, respectively, perpendicular to and along the Langer’s lines 7 . The maximum strains are lowest along Langer’s lines, as expected. The tensile curves show three regions, characteristic of many collagenous materials 13,33 : I–toe, II–heel and III–linear region. For comparison, the tensile response of isotropic, latex rubber is plotted in the inset of Fig. 3a this has a characteristic shape with an inflection point followed by a steep slope increase associated with entropic effects. In the dermis, collagen does not display this behaviour indeed, there are significant differences between the plots of the two materials. In the skin, the slope increases monotonically with increasing strain, until the linear region is reached. The skin shows higher strength (

15 MPa) at the strain rate of 10 −1 s −1 , than at the strain rate of 10 −3 s −1 (

8 MPa), the maximum stress decreasing from the prominence of interfibrillar sliding at low strain rates. Polymeric chains in rubber, conversely, are connected by strong bonds (for example, vulcanization) such that stretching of the structure is dictated by other mechanisms. In collagen, higher strain rates leave less time for interfibrillar sliding and owing to increased viscous forces, the fibres can carry more stress. These results are consistent with human skin tested parallel and perpendicular to Langer’s lines 34,35,36 the strength was also higher (

17–28 MPa) and the maximum strain lower (

0.5–0.6) parallel to the Langer's lines, compared with the corresponding strength (

0.4) perpendicular to the lines.

(a) Stress-strain curves of rabbit skin in longitudinal (parallel to backbone, perpendicular to Langer’s lines) and transverse (perpendicular to backbone) orientations, at strain rates of 10 −1 (red band) and 10 −3 s −1 (blue band). Skin displays higher strength at higher strain rates. Inset shows tensile response of latex, with much higher tensile strains determined by the degree of vulcanization. (b) Modelling of stress-strain curves of skin with Castigliano's therom (dashed lines) and by experiments using steel wire, composed of segments of circles (full lines). (c) Steel wire before and after stretching. The wire curvature (shown in schematic drawing) is defined by the central angle θ0 (

30° to 130°), which determines the maximum strain. Experimental and mathematical predictions indicate good agreement reflecting the characteristic response of skin.

Constitutive response and modelling

We modelled the tensile stress-strain response of skin by using a steel wire composed of circular segments. This new model is superior to the use of a sine-function 18,27 , zig-zag 37 or a helical shape 16,17 because opposite segments are always continuous, independent of the radius moreover, it enables analytical solutions to be derived. Sections of semicircles were connected consecutively, a geometry which is pertinent as there are no discontinuities in slope this form accurately represents the in vivo arrangement of collagen. This is preferable to previous approaches because of its ability to control the maximum attained strain while maintaining an accurate representation of the skin. Supplementary Fig. 1 further justifies the selection of the chosen shape. Figure 3c shows one example of the collagen shape. The maximum strain is determined by the angle θ that defines the circular segments, increasing with rising θ. For instance, the maximum strain corresponding to a total rectification of the segments at an angle θ=90° is equal to 0.57. θ is the central angle of one quarter of the model circular segments with central angles of 30°, 50°, 70°, 90°, 110° and 130° for a radius r of 120 mm were used to model the shapes of the collagen. Fig. 3c shows the metal wire in the initial and fully stretched configurations. We used Castigliano’s theorem 38 to derive the stress, σ0 (normalized by the Young’s modulus, E), which we compare with the experimental results from steel wires, shown by the solid lines in Fig. 3b. Specifically, the extension of the steel spring was analysed assuming a purely elastic response of circular beam segments in tension:

where E′ is a pseudo-modulus (determined from the geometric shape of the wire), θ0 is the initial central angle of the 1/4 circular segments (Fig. 3b) and rc is the initial circle radius. The strain increment, , can be obtained directly from the change in radius r as the segment is stretched:

The dashed lines in Fig. 3b show the model predictions from equations 1 and 2.

The time-dependent component can be expressed by the Maxwell model, with the elastic spring (equations 1 and 2) and a dashpot in series. The viscous contribution is due to hydrogen bonding between the fibrils, which, on being disrupted and reformed, allows their time-dependent sliding.

To include the non-elastic terms from interfibrillar sliding, we assume a simple spring/non-linear dashpot series model where the total strain εt is given as the sum of the elastic εel and viscous εη strains: εt=εel+εη. The viscous term can be represented by a simple Newtonian response: , where η is the Newtonian viscosity, such that the viscous strain is given by:

It is simpler to use a polynomial fit to the elastic constitutive equation of the form , where A, B, C and D are fitting constants, leading to:

where is the strain rate. We should emphasize that the viscous component comes from the breaking of interfibrillar bonds, which results in sliding between them. Thus, the fractional area where viscous flow takes place is a small number as such, the viscosity used in equation 4 is an ‘effective’ viscosity. The resulting stress-strain response of the wire is modified as a function of viscosity (at a constant strain rate) in Fig. 4a, and strain rate (at a constant viscosity) in Fig. 4b. These calculations show in schematic manner how the viscosity influences the mechanical response. As the samples dry, the viscosity increases and the overall response is altered. This is predicted by the modelling of Gautieri et al. 39 , as shown in the Supplementary Discussion.

(a) Effect of viscosity on the stress-strain response of a non-linear elastic material. (b) Effect of strain rate, at a constant viscosity, purely elastic response at 10 −3 s −1 . (c) Actual skin has a hierarchical structure spanning the nanoscale of twisted peptide chains to the microscale of wavy collagen and elastin fibres. The proposed wire model only addresses structure at the

50 nm to 10 μm dimensions, as depicted by levels II and III in the schematic. Blue dots in II represent hydrogen bonds and water molecules.

The wire model is a simple representation of almost two levels of the hierarchy of the skin. Figure 4c shows four levels of such hierarchy (considering primarily collagen), specifically: I (sub-nanometre) level—collagen molecule, II (nanometre) level—collagen fibrils, III (micrometre) level—collagen fibres, arranged in a ‘curvy’ geometry, and IV (mesoscale) level—collagen fibres with two orientations creating a fabric with orthotropic response. More complex models can be developed 40 but for the purposes of this analysis the one presented in Fig. 4c suffices. The model focuses on levels II and III. Translating this to the mesoscale in level IV, and incorporating anisotropy, can provide the orientation-dependent mechanical response between the orthogonal axes ϕ=0 (direction of the Langer's lines) to 90° (perpendicular direction) in terms of the strains in directions x1 and x2 by:

where f1 and f2 are different functional dependencies of the stress. This leads to predictions of the stress-strain response as a function of the orientation in the skin, as described in the Supplementary Discussion section, specifically in Supplementary Fig. 2, which captures the essential features of the experimental data in Fig. 3a.

Synchrotron X-ray characterization

We used in situ SAXS 41 with a synchrotron X-ray source to investigate this reorganization of the collagen fibrils in the skin during tensile loading, combining these data with in situ structural observations of the collagen behaviour in the environmental SEM under stretching. SAXS has been used previously to study collagen 18,42,43 , specifically the uniaxial and biaxial directional stretch of bovine pericardium and the collagen structure at different temperatures and degrees of hydration. Here, we determined a stress-strain curve for skin exhibiting the three characteristic toe-, heel-, and linear-shaped regions 8,13,44 (stages I–III) with a stage IV representing failure (Fig. 5a–e). The first three stages display a characteristic J-shape, which has been seen for collagen in other organs 8,11,12,13 . Each point on the curve represents a SAXS measurement during tensile loading with 13 points exposed to X-rays. The four data points at the ends of the red dashed line arrows in Fig. 5e are used to discuss the structural changes shown in Fig. 5a–d. In the diffraction patterns of the four points (Fig. 5a–d), the arcs represent the distributions of orientation of the collagen fibrils the radii of the arcs indicate their d-spacing evolution. Figure 5f,g show, respectively, the evolution of the central angle of orientation of the collagen fibrils and their d-spacing. Evaluation of the results in Fig. 5, combined with in situ SEM observations (Fig. 6), permits the identification of the four salient mechanisms underlying the tear resistance of skin during tensile straining—in four stages marked I–IV in Fig. 5f,g.

Variation in SAXS peak-intensity, orientation angle, collagen fibril d-spacing and full-width-at-half-maximum (FWHM), from tensile tests on rabbit skin. (ad) Diffraction patterns: arcs show orientations of fibrils, images of the sample shown at top-right corners, (a) collagen fibrils randomly oriented to tensile axis, shown by constant intensity of diffraction pattern circles, (b) fibrils become gradually aligned in tension direction, (c) fibrils aligned along tensile axis, (d) fibrils fractured and relaxed. (e) During tensile test, 13 stress-strain data points (black dots) were recorded at 5 s intervals four stages were identified. (f) Angle of normal to the tensile axis (black dots) versus intensity of fibrils (blue dots) as a function of strain, and (g) d-spacing (black dots) and FWHM (blue dots) of fibrils as a function of strain. Four stages: I-toe and II-heel, curved collagen fibrils straighten, rotate, stretch (d-spacing increases), III-linear, fibrils continue to rotate and stretch, orienting completely along tensile axis (angle=0°), but also slide and delaminate IV-fracture, fibrils fracture and curl back (angle deviates from 0°, d-spacing, FWHM and intensity decrease).

SEM images (ad) and schematic drawings (eh) of the mechanisms during the four stages of tensile loading of rabbit skin, black arrows in a and e represent the direction of tension testing. (a,e) Curved collagen fibrils are oriented along the tensile axis (b,f) collagen fibrils are straightening, larger and larger amount of the fibrils re-orient close to the tensile axis (c,g) collagen fibrils are stretching, sliding, delaminating and orientated completely along the tensile axis (d,h) collagen fibrils are fractured and curled back. Scale bars in ad are 20, 20, 20, 50 μm, respectively.

Stage I and II (toe and heel)

The skin was moderately stretched before loading because of the gravity acting on the wet samples. No clear mechanistic distinction was observed in stages I and II, since due to the dose limit, only three data points were obtained. The diffraction pattern in Fig. 5a (at the beginning of tensile testing) displays almost a continuous circle, suggesting that the collagen fibrils are arranged at widely varying angles. During these stages, the collagen fibrils straighten (Fig. 6b,f) and rotate towards the tension axis (Figs 5f and 6a,e). The fibrils also stretch, as the collagen d-spacing increases (Fig. 5g). Despite the increasing strain, the toe and heel stages show little increase in stress, consistent with the wire model data, which suggest that during this period more strain is taken up by straightening than by stretching.

Stage III (linear)

The collagen fibrils continue to rotate, as α (fibril angle with the tension axis) drops from

0°. The fibrils also become more uniformly aligned, with Herman’s orientation factor increasing from 0.24 to 0.76 (data not shown). Herman’s orientation factor defined as ½(3cos 2 Φ−1), where Φ is the angle between the orienting entity and fibre axis, quantifies orientation on a scale from 0 (random distribution) to 1 (perfectly oriented/aligned). This is seen visually as the SAXS peak transforms from a circle to an oriented arc (Fig. 5a–c). This peak correspondingly grows in intensity (Fig. 5f), which also reflects the recruitment of greater numbers of fibrils into common alignment. The realignment of the collagen fibrils possibly increases the modulus locally, which would elevate local stress and precipitate failure at this stage. Simultaneously, the d-spacing of collagen fibrils increases from 64.5 to 66.9 nm, indicating that the collagen is still extending elastically. However, this small elastic strain of

0.037 is not sufficient to accommodate the applied strain, which can be as high as 0.5 in this stage. Hence, the mechanisms of inter- and intrafibrillar sliding become major contributors to accommodate the imposed strain. Delamination of collagen fibrils is observed (Fig. 6c), consistent with the SAXS peak becoming broader (full-width-at-half-maximum (FWHM) increases, Fig. 5g), owing to the defects introduced into the previously well-ordered fibrils. In this stage, the main mechanisms are reorientation, stretching, sliding, and delamination of collagen fibrils (Fig. 6e,g).

Stage IV (fracture)

In stage IV, the collagen fibrils fracture and curl back upon unloading (Fig. 6d). The fibrils return to a wider range of orientations, so that the SAXS peak concomitantly decreases in intensity, and the central angle of orientation drifts away from the axis of tension. Owing to unloading, the collagen d-spacing (Fig. 5g) and the FWHM of the SAXS peak both decrease, as the fractured collagen returns to a shorter and more well-ordered d-spacing.

Thus, multiple mechanisms operate in the collagen under tensile loading to provide skin with its extraordinary tear resistance: rotation, straightening, stretching, sliding and delamination. The first three mechanisms provide the strain to induce large shape changes within the elastic regime these mechanisms also permit the re-alignment of collagen around any tear in the skin to ensure its blunting.

In conclusion, we have shown the remarkable tear resistance of skin to be associated with specific mechanisms within the collagen. This behaviour, especially the ability of collagen fibrils to slide past each other, contrasts with natural rubber vulcanizate, where ‘nicked’ specimens will readily tear at low loads 45 . Clearly, the role of collagen fibrils varies significantly in biological materials. In bone 29,46 , sliding between the collagen fibrils forms the basis of ‘plasticity’ and provides a bilinear uniaxial stress-strain response indeed, collagen fibrils interact with cracks contributing to toughness. In certain fish scales 47,48 , the Bouligand-type structure, with collagen fibrils oriented in different directions, acts as a tough foundation to the highly mineralized surface to provide resistance to both penetration and fracture. In such biomaterials, the collagen fibrils are mineralized and initially straight. In contrast, the collagen fibrils in the skin are initially curvy and highly disordered. We have shown how these curvy collagen fibrils act to enhance skin’s tear resistance through their rearrangement towards the tensile-loading direction, with rotation, straightening, stretching, and sliding/delamination before fracture. The rotation mechanisms recruit collagen fibrils into alignment with the tension axis at which they are maximally strong or accommodate shape change (for example, blunting a tear) straightening allows strain uptake without much stress increase, sliding allows more energy dissipation during inelastic deformation. Such reorganization and sliding of the fibrils are responsible for stress redistribution (blunting) at the tips of tears and notches. It is the synergy of these four mechanisms that confers the extraordinary resistance to tearing in skin, which in itself is a requisite for the survival of organisms.


Measuring Sensitive Circuits

If you're measuring resistance in electronic circuitry, you generally need the most sensitive range the meter offers, which is the one designated 0-200 ohms or 1X. When using this range with an analogue multimeter, the value indicated by the pointer is the actual resistance. If you're using a digital multimeter, the meter will display its maximum number of decimal places. If the resistance is too high to be measured in this range, a digital meter will display an overload message, and the pointer on an analog meter will move too far to the left to give a meaningful reading. When this happens, you need to decrease the meter sensitivity.


MATERIALS AND METHODS

Fabrication of 3D printed shark skin

A freshly dead specimen of a male shortfin mako shark (I. oxyrinchus) with a total body length of 190 cm was obtained from fishermen near Boston, MA, USA. An area of skin

10 cm 2 was extracted using dissection instruments and carefully cleaned with a water jet. We then cut a smaller piece of skin (2×2 mm) from within this larger area and used a micro-CT scanner (Xradia VersaXRM-500, at Cornell University, Institute of Biotechnology) to scan the sample at a resolution of 1.583 μm in the x-, y- and z-directions. We picked a single representative skin denticle from this scan and constructed a 3D model, which was then covered in a digital mesh (Fig. 8A–D) using Mimics 3D modeling software (Materialise Inc., Leuven, Belgium).

The reconstructed denticle model was duplicated and linearly arrayed in a controlled pattern on a membrane substrate (Fig. 8E–G) in SolidWorks (SolidWorks Corp., Waltham, MA, USA). The parameters governing denticle spacing, which determine the distribution and position of denticles on the membrane, are provided in Fig. 8F,G. From the lateral or side view (Fig. 8F), the ridge tips of the denticles can be seen slightly overlapping the base of the next posterior denticle. All denticles penetrate into the membrane substrate and form an anchor-like structure as seen in the skin of a real mako shark (Motta et al., 2012). To fabricate a synthetic shark skin membrane, we used an Objet Connex500 3D printer (Stratasys Ltd, Eden Prairie, MN, USA), which uses multiple nozzles to print materials with different mechanical properties and colors. With this technology, we were able to use two different materials for fabricating a shark skin model that contained both rigid (for the denticles) and flexible (for the membrane substrate) parts. The Young's modulus for the rigid and flexible regions was about 1 GPa and 1 MPa, respectively. In addition, an easily removable support material was used to allow fabrication of overhanging denticles by providing a temporary surface to support 3D printing of the denticle crown.

This supporting material was carefully removed by water jet after the entire shark skin membrane was printed. It should be noted that the bio-inspired ‘anchor’ structures allow the denticles to remain undamaged and intact after being flushed with a strong water jet used during removal of the support material. This also ensures that the denticles remain firmly attached to the membrane substrate during locomotion and movements controlled by the mechanical flapping device. The Objet Connex500 printer, however, did not allow the denticles to be printed at-scale (150 μm denticle length, Fig. 1) because of limitations on printing resolution: tests of at-scale 3D printing showed an unacceptable degradation of fine denticle structure. Therefore, we scaled the denticle gradually up from its original size (Fig. 8A–C) until we obtained an acceptable size at which all 3D features of the denticle were identifiable. After a series of tests, synthetic denticles with clearly discernible 3D features such as the three surface ridges were obtained when the at-scale denticle model was magnified 12.4 times. In Fig. 9A, a wide-field scanning electron microscope (SEM) image of the 3D printed shark skin in a curved state is provided. The concave and convex structures on the membrane demonstrate its flexibility. Alterations in denticle overlap between the convex and concave regions are easily seen, and illustrate the effect on denticle spacing when the membrane substrate is curved compared with the printed skin in the flattened state (Fig. 9B). A single 3D printed denticle is shown in Fig. 9C. Dimensional scaling of the 3D printed skin relative to natural shark skin denticles is addressed below, where we show that they operate at a similar S+ region (Eqn 3) in our dynamic testing program despite the denticle size difference. In addition, we note that some shark species possess denticles that approach 1 mm in size (Castro, 2011), and thus our current 3D print resolution will be at-scale for future studies of other shark species.


Types of Electrode: 4 Types (With Diagram)

This article throws light upon the four types of electrode used in electrochemical techniques.

The four types of electrode are: (1) The pH Electrode (2) Ion Selective and Gas Sensing Electrodes (3) The Clark Oxygen Electrode and (4) The Leaf Disc Electrode.

Type # 1. The pH Electrode:

Principles:

Perhaps the most convenient and accurate way of determining pH is by using a glass electrode. The pH electrode depends on ion exchange in the hydrated layers formed on the glass elec­trode surface.

Glass consists of a silicate network amongst which are metal ions coordinated to oxygen atom, and it is the metal ions that exchange with H + . The glass electrode acts like a battery whose voltage depends on the H + activity of the solution in which it is immersed.

The size of the potential (E) due to H + is given by the equation:

where [H + ] and [H + ]o are the molar concentrations of H + inside and outside the glass electrode respectively. In practice, [H + ] is generally 10 -1 , because the electrode contains 0.1 M HCL. Since pH= – log [H + ], it follows that the developed potential is directly proportional to the pH of the solution outside the electrode. Glass electrodes are particularly useful because of lack of interfer­ence from the components of solution.

On the whole these molecules are not readily contaminated by molecules in solution, and if other ions are present they do not cause any significant interference. However, at high pH they do respond to sodium. Inaccuracies also occur under very acid condi­tions.

A glass electrode consists of a thin, soft glass membrane that is situated at the end of a hard glass tube, or sometimes an epoxy body. Also present in the glass electrode is an internal reference electrode of the silver/silver chloride (Ag/AgCL) surrounded by electrolyte of 0.1 M HCL. This internal reference electrode gives rise to a steady potential.

Thus the varying potential of the glass electrode can be compared with a- steady potential produced by an external reference electrode such as the standard calomel electrode by joining internal and external reference electrode.

The external reference electrode can either be a separate probe or built around glass electrode giving a combination electrode. If a combination electrode is used, the level of the test solution must be high enough to cover the porous plug (liquid junction) but not as high as the level of salt bridge solution (KCL) in the external electrode because it is essential for KCl to diffuse out slowly into the test solution.

Whatever reference electrode is used the measured voltage is the result of the difference be­tween that of the reference and the glass electrodes. In practice, however, there are other potentials present in the system. These include so-called asymmetric potential, which is poorly understood but which is present across the glass membrane even when the H + concentration is the same on both sides.

Also included are the potentials due to Ag/AgCl and to the liquid junction to the reference electrode, which gives the potential because the K + and CI – do not diffuse at exactly the same rate and, therefore, generate a small potential at the boundary between the sample and the KCl in the reference electrode. The measured potential for glass electrode should thus also include constants to account for the additional potential within the device.

Therefore, the equation becomes:

where E* includes the standard electrode potential for glass electrode, and the constant junction potential present in the system.

At 25°C this equation becomes:

where E* now also includes a term to account for the internal H + concentration. As already known there is a 59 mV change for a 10-fold change in the activity of a monovalent ion this means that a change of one pH unit produces a 59 mV change.

A pH electrode is used in conjunction with a pH meter. This records the potential due to H + concentration but is designed to take a little current from the circuit. A large current flow will cause changes in the ion concentration and hence changes in pH this is pre­vented by having a high resistance present. The pH meter, glass electrode and reference calomel electrode are designed so that pH gives a zero potential.

Operation Of pH Electrode/Meter:

pH electrodes are available in variety of different shapes and sizes for many different applications. Intracellular pH can also be measured by using a miniature probes (micro electrodes). However, majority of them are based on same principle and operated in a similar fash­ion.

It is important that the outer layer of glass on glass electrode remains hydrated, and so it is normally immersed in a solution. Thus thin glass layer is fragile and thus care must be taken not to break it or scratch it, or to cause a buildup of static electric charge by rubbing it. Gelatinous and protein containing solutions should not be allowed to dry out on the glass surface as they would inhibit response.

As it is clear from above equations that potential produced is temperature depend­ent (each pH unity change represents 54.2 mV at 0°C and 61.5 mV at 37°C). This effect is predict­able and can be compensated for. The pH meter will thus have a temperature compensation dial that must be correctly set before the meter is calibrated.

Calibration will necessitate the use of two solutions of widely differing pH. Usually calibration is first performed with buffer of pH 7, followed by a pH 4 buffer (if the sample is expected to be a acid) or a pH 9 buffer (if the sample is expected to be basic). Once the pH electrode is calibrated, it can simply be immersed in the solution to be measured and a rapid and accurate measurement estimate of pH can be made.

Type # 2. Ion Selective and Gas Sensing Electrodes:

The glass pH electrode is really a kind of ion-selective electrode (ISE) that is sensitive to H + . Similar potentiometric electrodes have been developed which are responsive to other ions, e.g., Na + , NH + 4, Cl – and NO – 3. The active material within these devices may be glass, an insoluble organic salt, or an ion exchange material.

Glass is the active material within the pH electrode, but modified aluminium silicate glasses can also be used to produce a variety of monovalent cation responsive electrodes. Insoluble inorganic salts like silver sulphite can be used to produce electrodes responsive to Cu 2+ , Pb 2+ and Cd 2+ , whereas lanthanum fluoride may be used to produce electrodes responsive to F – .

Ion selective electrode responds to the activity of particular ion. However, if the instrument is calibrated with a standard of known concentration then, provided the ionic strength of solution are similar, the concentration of test solution will be recorded. If some of the ions are not free and exist in complex form or an insoluble precipitate, these electrodes will give a much lower reading, then with a method that detects all of the ions present. Generally used ion selective electrodes are Ca 2+ , K + , and NO – 3.

An electrode may be ion selective but not ion specific. As with glass electrodes, these can be fouled by proteins forming a surface film. A reference electrode is also needed with these ISE so that the varying potential of these ISE can be compared with the steady potential produced by reference electrode.

Gas Sensing Electrodes:

They are used generally to estimate the concentration of gas by its interaction in a thin layer surrounding an ion sensitive electrode, commonly a pH electrode. Carbon dioxide, sulphur dioxide, ammonia can all be measured by their dissolution in a thin layer surround­ing the pH electrode, and measuring the resultant pH of the layer.

Miniaturisation and Applications of Ion Sensitive Electrodes:

Miniaturisation of ion selective electrodes has been achieved by modification of field effect transis­tor to respond to specific ions. Such ion selective field effect transistors (ISFETs) are likely to have great clinical value. Multifunctional ISFETs are already available which are used to measure pH, Na + , K + , and Ca 2+ .

Type # 3. The Clark Oxygen Electrode:

It consists of a platinum cathode and silver anode, both immersed in same solution of saturated potassium chloride and separated from the test solution by a oxygen permeable membrane. When a potential difference of—0.6 V is applied across the electrodes such that platinum cathode is made negative with respect to silver anode, electrons are generated at anode and are then used to reduce oxygen at cathode.

The oxygen tension at cathode drops and so to make this deficit more oxygen moves towards cathode. Since the rate of diffusion of oxygen from the membrane is the limiting step in the reduction process, the current produced by the electrode is proportional to the oxygen tension in the sample.

These electrode reactions may be summarized as under:

At silver anode 4Ag + CI ‑ → 4AgCl + 4e –

At platinum cathode O2 + 4H + + 4e – → 2H2O

Operation of Rank Oxygen Electrode (Clark Electrode):

These allow the sample to be placed in upper reaction chamber by an oxygen permeable and ion impermeable membrane. Teflon is the usual choice, though cellophane, polythene, silicon rubber and cling film have been used with varying degree of success. Care must be taken that membrane must not become contaminated.

Thinner membranes give more response but are more fragile. The membrane covers the electrodes and allows oxygen to diffuse towards them whilst preventing other reaction elements to reach electrode and poison them. The electrodes are maintained in elec­tric continuity with potassium chloride solution.

Oxygen electrode is mounted above a stirring motor, which is able to rotate a magnetic fol­lower (flea) when inserted into the reaction vessel which is important as the platinum cathode reduces oxygen to produce the electric current. A correct set-up will show reduction in current when stirrer is switched off due to depletion of oxygen in the potassium chloride filled electrode chamber.

Resumption of stirring will result in a return of current (oxygen tension in potassium chloride) to its previous level prior to the stirrer being switched off. Since both solubility and rate of diffusion is affected by temperature, therefore some form of temperature control is necessary for better results which are done by circulating water bath.

Calibration of the instrument should be carried out at the same temperature as that of experiment. Many chemicals are adsorbed onto the surface of the membrane and reaction vessel hence it is important that the apparatus is thoroughly cleaned after each experiment.

Applications of Rank Oxygen Electrode:

Due to their ability to give continuous trace, oxygen electrodes have largely replaced manometric techniques in the study of reactions involving oxygen uptake and evolution.

i. Mitochondrial studies:

The study of respiratory control and effect of inhibitors on mitochondrial respiration and the measurement of phosphorylation: oxidation (P: O) ratios are best done by oxygen electrodes.

ii. The sites of action of electron transport inhibitors can also be determined using an oxygen electrode.

iii. Micro-organism that uses oxygen as the terminal electron acceptor of respiratory elec­tron transport can be studied using oxygen electrode and the effect of electron transport inhibitors determined.

Enzymes are readily studied using Clark oxygen electrode, provided oxygen is involved in the reaction. Glucose oxidase, D-amino acid oxidase, and catalase are examples whose properties can be studied in this way.

Probe Type Clark Electrode:

These rely on same principle of operation as the rank electrode. However, the cathode and retain­ing membrane are arranged at the end of the probe to enable insertion into a liquid phase. It has disadvantage that it does not have stirring arrangements. It has a variety of uses.

Measurement of oxygen in bulk liquids:

Oxygen concentrations are routinely monitored in fermentation processes, sewage and industrial waste treatment and in inland, coastal and oceanic waters. This involves the variation of the Clark electrode called flush top sensor.

Early clinical use of oxygen electrode is to measure heart-lung machines during open heart surgery. They are also used for testing patients who were treated with oxygen. Small samples of blood are taken from patient and oxygen content is measured in a small Clark type pO2 electrode.

Type # 4. The Leaf Disc Electrode:

Whilst the rank oxygen electrode is ideally suited to many applications requiring a measurement of oxygen in aqueous samples, a leaf disc electrode such as the Hanasatech LD2 is of more use if gaseous oxygen measurement is required. Since the measurement of oxygen evolution is one of the easiest ways of following photosynthetic process in leaves, this instrument has found much biologi­cal application.

This device measures oxygen amperometrically using the same principle as the rank electrode. However, instead of being a liquid -filled reaction vessel, the reaction chamber is designed to allow a leaf to be held in place and provided with saturating carbon dioxide (or bicarbonate as a source of carbon dioxide). Illumination is usually provided by an array of light-emitting diodes (which produce little heat) and the oxygen emitted by leaf during photosynthesis can be measured.

Calibration of this electrode is bit complex as compared to rank electrode. A zero oxygen signal can be produced by passing nitrogen through the reaction chamber. Once this is stopped and air is passed through the chamber, signal corresponding to 21% of the oxygen can be determined. However, in closed chamber system, the amount of oxygen is related to the oxygen concentration and to volume of the chamber.

In practice, because the leaf disc itself may reduce the effective volume of the chamber, calibration involves injecting known volumes of air into the chamber and measuring the voltage response to obtain the effective volume of the chamber and hence a precise calibration of the electrode.

The leaf disc electrode has been used extensively for the study of the relationship between photosynthetic oxygen evolution under saturating carbon dioxide and the intensity of illumination, enabling calculation of quantum yield, the inclusion of probes to measure emitted fluorescence from the leaf disc at the same time as the oxygen evolutions measurement are made has resulted in a device that provides variety of information.

Applications of these devices are diverse, ranging from studies of micro-propagated plants to those plants suffering from atmospheric pollution. Though leaf disc electrode is clearly designed for whole leaf studies, photosynthetic rates of microalgae have also been studied using theses electrodes.


Availability of data and materials

The sequencing data from this study have been deposited in the CNSA (https://db.cngb.org/cnsa/) of CNGBdb with accession number CNP0000635 and NODE (https://www.biosino.org/node/index) with accession number OEP001168. A website (https://db.cngb.org/microbiome/genecatalog/genecatalog/?gene_name=Human%20Skin%20(10.9M)) has been set up to better visualize the annotation information of the gene catalog and guide researchers who are interested in using our data set and downloading specific sets of data.


Introduction

Recent exponential advances in genome sequencing technologies have enabled a detailed map of genomic alterations identified in human cancer populations. Several multi-center cancer exome/genome projects, such as The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), have significantly improved our understanding of the landscape of somatic alterations that promote tumorigenesis and tumor evolution [1–4]. Yet, the annual number of innovative anticancer agents approved by the U.S. Food and Drug Administration (FDA) has not increased significantly in the past few years compared to one or two decades ago [5]. There is a pressing need to develop new technologies, such as computational tools, to accelerate the modern oncology drug discovery and development by exploiting the wealth of large-scale exome/genome sequencing data in the genomics era from the evolutionary medicine perspective [6].

Somatic alterations identified in tumor exomes/genomes are commonly grouped into two classes: gain-of-function mutations on oncogenes and loss-of-function mutations on tumor suppressor genes (TSGs). Although inhibiting proteins encoded by oncogenes with small molecules or monoclonal antibodies have been proven to be effective in the clinic, it is challenging to inhibit the function of multiple undruggable oncogenes (i.e., KRAS and c-Myc) and the emerging drug resistance. In addition, restoring the function of TSGs that are highly mutated or deleted in tumor cells by traditional small molecular drug is not feasible. Recent efforts to map genetic interactions (e.g., synthetic lethal interactions) in tumor cells have suggested that tumor vulnerabilities from evolutionary medicine perspective can be exploited for development of novel molecularly targeted therapies [7–14].

In the context of genetic studies, a synthetic lethal interaction involves two genes: the cell is viable upon perturbation of either gene alone, but simultaneous perturbation of both genes by genetic or genomic alterations will result in cell death [9]. A synthetic lethal interaction occurring between a tumor-specific somatic mutation and a gene that drives tumorigenesis and tumor progression offers an ideal therapeutic target in cancer [10]. Furthermore, discovery of synthetic lethal interactions through identification of a second-site synthetic lethal druggable target facilitates indirect targeting of tumor alterations of undruggable proteins (e.g., KRas or p53) [7–9]. Recent advances in functional genomic technologies, such as RNA interference (RNAi) or CRISPR-Cas9 assays, have offered innovative tools to screen human cancer cells for genetic interactions. By systematic application of CRISPR-based screens, Wang et al., uncovered PREX1, a key synthetic lethal interactor of oncogenic Ras in human acute myeloid leukemia cell lines [8]. However, measurements of cell proliferation in genome-scale CRISPR-Cas9 loss-of-function screens have a potentially high false-positive rate in copy number-amplified regions [15, 16]. Furthermore, large-scale experimental assays are expensive and time-consuming. Computational approaches with low cost and high efficiency offer new tools for genome-wide identification of cancer genetic interactions and for inferring tumor evolution through analyzing publicly available large-scale tumor exome/genome sequencing data [17, 18]. For example, several computational approaches, such as MEMo [19] and WeSME [20], were reported to identify mutually exclusive mutations in cancer.

In this study, we propose a novel computational methodology, termed Individualized Network-based Co-Mutation (INCM), for comprehensive identification of putative genetic interactions that drive tumorigenesis and anticancer drug responses. The central hypothesis asserts that network-based co-mutation analysis of individual tumors may identify putative genetic interactions that promote tumorigenesis and tumor evolution, offering potential targets for the development of molecularly targeted therapies. Specifically, we applied INCM to over 2.5 million nonsynonymous somatic mutations derived from 6,789 tumor exomes across 14 cancer types from TCGA. We computationally identified hundreds of new putative genetic interactions in multiple cancer types via INCM. As proof-of-concept, we showed a higher genetic interaction burden mediated by significantly mutated genes in cancer populations, experimentally validated cancer genes, chromosome regulation factors, and DNA damage repair genes, in comparison to pan-cancer essential genes identified by CRISPR-Cas9 screenings in 324 cancer cell lines across 30 cancer types. Via INCM, we constructed cancer type-specific genetic interaction subnetworks for 14 cancer types respectively. We showed that network-predicted putative genetic interactions offer potential therapeutic targets and can be used to predict patient survival and drug responses. Put together, this study offers a generalizable network-based framework in identifying potential therapeutic pathways for personalized cancer medicine by targeting tumor vulnerabilities.


Introduction

Hand therapists record any changes prior to and following treatment by measuring joint angles. Proper measurement of joint movement in daily physical activities over long periods of time is therefore a topic of interest. Three-dimensional (3D) motion analysis systems [1,2] and instrumented gloves have been used for dynamic recording of finger bending angles during the performance of daily activities [3]. Such 3D motion systems can capture complex movements accurately but are bulky and expensive and have large space requirements they are therefore less suitable for routine clinical use. Instrumented gloves that utilize resistive bend sensors [4] have been developed for application in fields such as computer gaming, virtual reality, rehabilitation, and robotics. Although these gloves are cheaper and easier to set up, they can be cumbersome and require a tedious calibration process furthermore, the cloth support has been reported to adversely affect measurement performance [5].

Recently, stretchable electronic devices have attracted attention in interesting research areas such as artificial skin, human-interactive devices, and soft robotics [6–8]. Among such devices, a stretchable strain sensor can be considered the most useful owing to its applicability in various fields such as rehabilitation, personal health monitoring, and human motion capture. Flexible and stretchable sensors can be easily embedded into clothing or even attached directly onto human skin. Any applied strain leads to microstructural deformation of the sensor, which, in turn, causes a change in its electrical resistance. The sensor detects resistance changes, and it can thus measure acceleration, pressure, tension, and strain.

Stretching and contraction movements of human joints generate strains as high as 55%, and strain sensors that are capable of detection of such high strains are in high demand [7]. Commercially available strain sensors based on metal foils and semiconductors have extremely poor stretchability (≤5%) and consequently low conformity to biological tissues. Fabrication of stretchable strain sensors with high sensitivity, high durability, fast response, and excellent stability is necessary for the evaluation of human joint motion. For the realization of novel strain sensors that can overcome these issues and meet these requirements, nanomaterials such as carbon nanotubes (CNTs), graphite, and nanowires have been studied. Among such sensors, those based on CNTs have been reported to exhibit excellent electrical and mechanical properties because of the unique molecular structure of CNTs, which makes them suitable for the fabrication of stretchable electronic devices.

Various fabrication methods such as stacking [8], dry-spinning [9], transfer [10], and polymerization of nanocomposites [11–13] have been studied to take advantage of the unique properties of CNTs. For example, Yamada et al. [8] assembled CNT sensors on stockings, bandages, and gloves and demonstrated the ability of the resultant fabricated devices to detect different types of human motion, including movement, typing, breathing, and speech they therefore concluded that these sensors are promising for use in health care and rehabilitation. However, improvement of the strain sensitivity of CNT-based strain sensors remains a challenge. Stretchable strain sensors composed of CNT films exhibit a piezoresistive response because of the occurrence of a cracking phenomenon under applied strain. Microcracks are formed in a CNT film under stretching, whose density increases with the applied strain and recovers to the initial value after release. The unique structure of CNTs makes CNT films more durable and less sensitive by suppressing crack propagation. Effective and controlled crack generation is necessary for the realization of a highly stretchable and ultra-sensitive strain sensor.

The aim of this study was to fabricate an inkjet-printed CNT strain sensor and evaluate its feasibility for the detection of finger joint motion. The inkjet-printing method provides ease of crack control as well as technical advantages such as precision, ease of patterning, low cost, and large-area scalability. The properties of the fabricated strain sensor were quantified via stretching and cycling strain tests. The excellent properties of the strain sensor enabled detection of finger motion. Because the human hand has multiple measurable joints, we believed that application of the strain sensor to finger joints would be appealing.


Assessment of Ripening Degree of Avocado by Electrical Impedance Spectroscopy and Support Vector Machine

Avocado, a climacteric fruit, exerts high rate of respiration and ethylene production and thereby subject to ripening during storage. Therefore, its ripening is a significant factor to impart optimum quality in postharvest storage. To understand the dynamics of ripening and to assess the degree of ripening in the avocado, electrical sensing technique is utilized in this study. In particular, electrical impedance spectroscopy (EIS) is found to uncover the physiological and structural characteristics in plants and vegetables and to follow physiological progressions due to environmental impacts. In this work, we present an approach that will integrate EIS and machine learning technique that allows us to monitor the ripening degree of the avocado. It is evident from our study that the impedance absolute magnitude of the avocado gradually decreases as the ripening stages (firm, breaking, ripe, and overripe) proceed at a particular frequency. In addition, principal component analysis shows that impedance magnitude (two principal components combined explain 99.95% variation) has better discrimination capabilities for ripening degrees compared to impedance phase angle, impedance real part, and impedance imaginary part. Our classifier utilizes two principal component features over 100 EIS responses and demonstrates classification over firm, breaking, ripe, and overripe stages with an accuracy of 90%, precision of 93%, recall of 90%, f1-score of 90%, and auc of 88%. The study offers plant scientists a low cost and nondestructive approach to monitor postharvest ripening process for quality control during storage.

1. Introduction

Avocados receive an increasing attention for extending nutritional food choice and agribusiness in United States [1]. According to a recent report from the National Agricultural Statistics Service of United States Department of Agriculture, the value of U.S. avocado production measured $316 million in 2016-17 [2] and U.S. consumption of avocados increased significantly from 1.1 pounds per capita in 1989 to a record 7.1 pounds per capita in 2016. Avocado, being a climacteric fruit, has a high rate of postharvest respiration. Consequently, it is one of the most perishable fruits and has very limited shelf life. It is prone to biochemical and physiological deterioration during postharvest ripening accompanied by degradation of visual appearance. This postharvest loss poses the risk of loss of market value of the avocado. In addition, from the point of view of consumer industry, only optimum ripening state attributes to the most nutritional value and best taste of a fruit. Hence, a better understanding of ripening dynamics of avocado can play a vital role to the development of appropriate tool for better packaging, storage, and transportation process and consequently meet the demand of both agribusiness and consumer industry.

Conventional chemical and biochemical analyses conducted to investigate the fruit ripening are limited by factors such as processing time and destructive nature [3]. These methods are often laborious and expensive and require access to laboratory facility. Hence, these methods prove to be infeasible for a repetitive inspection. Therefore, it is essential to expand current technologies from different viewpoints. A nondestructive, low cost, and easily accessible solution to this issue needs to be devised.

Nondestructive methods such as magnetic resonance imaging (MRI) and CT scan are found to be effective towards understanding of ripening, internal fruit quality, and postharvest processing [4, 5]. MRI method requires separation of signal of water proton from that of fat proton which is still a challenging task. And both MRI and CT are limited by the factors such as high cost and processing complexity. Hyperspectral imaging can effectively assess ripening degrees [6], but it also suffers from constrains such as cost and processing. Therefore, it is essential to expand current technologies from different viewpoints. On the contrary, electrical impedance spectroscopy (EIS) is a fast, low cost, and nondestructive method which is found to offer insight into plant physiology and physiological dynamics due to environmental impacts. In this direction, the EIS studies have been conducted as a nondestructive evaluation method to investigate the impedance spectrum variations and to determine the ripening degree in the avocado.

To develop an easily accessible and nondestructive method to understand mechanisms of ripening and to assess ripening degree of the avocado, the prospect of EIS technique is explored in this paper. This work on the avocado mainly focuses on the investigation of feasibility of EIS for assessment of the ripening degree nondestructively. The rest of the paper is organized as follows: related past works on application of EIS technique is reviewed in the Literature Review section. The next section introduces the theory of bioimpedance and electrical impedance spectroscopy. Later on, experimental methods and materials are illustrated. After that, the experimental and simulated results are presented and discussed, and finally, paper is concluded including some future exploration directions.

2. Literature Review

Impedance sensing technology especially EIS has emerged a new era into food quality and stability over the last decades. It has been extensively used in the field of plant physiology, agriculture, and food engineering for quality control and assessment of fruits and vegetables such as banana [7], Garut citrus [8], kiwi [9], lettuce [10], nectarine [11], and strawberry [12]. In order to assess the freshness of banana, EIS investigation was performed during different ripening states [7]. By attaching Ag/AgCl electrode and injecting a small amount of current, impedance responses are measured by the 4294 A impedance analyzer over a frequency range of 50 Hz to 1 MHz. The impedance magnitude, phase angle, real part, and imaginary part varied markedly with the alteration of the ripening state.

González-Araiza et al. [13] designed a nondestructive device to obtain the impedance spectrum of the whole strawberry fruit and later on performed classification by utilizing corresponding equivalent circuit parameters (constant phase element, CPE-P, and Rinfinity). The study showed that the strawberries at the highest stage of ripeness had significantly lower constant phase element and Ro (related to extracellular) values compared to other strawberries.

Neto et al. [14] utilized EIS technique for the determination of the maturation degree of mangoes based on variation of bulk resistance dependence with maturation of fruits. They came up with this strategy to normalize bulk resistance by diameter to compensate the size variations of samples. They demonstrated good agreement between variation of electrical response and mechanical response of fruit.

Montoya et al. [15] investigated that electrical conductivity could be a suitable factor for assessment of quality during ripening and cold storage. They found some resemblances between electrical conductivity response and ethylene productions curve. They defined a threshold of conductivity (0.24 S/m) that indicates the limiting value for fruit stored at noninjurious temperatures and subsequently transferred to 20°C for marketing.

Chowdhury et al. [16] carried out EIS study on the mandarin orange fruit during ripening in a spectrum between 50 Hz and 1 MHz. They observed significant variation of the impedance, phase angle, real part, and imaginary part of the impedance with different states of orange ripening. The study also demonstrated loss of weight of corresponding samples with the progression of ripening states. Thus, electrical sensing specially EIS technique was found to offer insight into physiology of fruits and vegetables undergoing the ripening process.

3. Theory of Bioimpedance and Electrical Impedance Spectroscopy

The plant body is a complex biological structure composed of tissues which are developed with cells suspended in extracellular fluids (ECF) [17]. Again, cells are composed of intracellular fluids (ICF), cell membrane (CM), and cell wall (CW). ECF, ICF, and CM are developed with different materials and so exhibit distinguishable electrical attributes. The ECF and ICF act as electrolytes and provide a conducting path to applied alternating current [18]. The CM is a protein-lipid-protein (P-L-P) structure and exhibits capacitance to the current. Consequently, the overall response of the biological tissues to an alternating electrical signal generates a complex sbioelectrical impedance. Mathematically, the impedance


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