Wearable Vector Electrical Bioimpedance System to Assess Knee Joint Health

Mid-Activity and At-Home Wearable Bioimpedance Elucidates an Interpretable Digital Biomarker of Muscle Fatigue

OBJECTIVE

Muscle health and decreased muscle performance (fatigue) quantification has proven to be an invaluable tool for both athletic performance assessment and injury prevention. However, existing methods estimating muscle fatigue are infeasible for everyday use. Wearable technologies are feasible for everyday use and can enable discovery of digital biomarkers of muscle fatigue. Unfortunately, the current state-of-the-art wearable systems for muscle fatigue tracking suffer from either low specificity or poor usability.

METHODS

We propose using dual-frequency bioimpedance analysis (DFBIA) to non-invasively assess intramuscular fluid dynamics and thereby muscle fatigue. A wearable DFBIA system was developed to measure leg muscle fatigue of 11 individuals during a 13-day protocol consisting of exercise and unsupervised at-home portions.

RESULTS

We derived a digital biomarker of muscle fatigue, fatigue score, from the DFBIA signals that was able to estimate the percent reduction in muscle force during exercise with repeated-measures Pearson's r = 0.90 and mean absolute error (MAE) of 3.6%. This fatigue score also estimated delayed onset muscle soreness with repeated-measures Pearson's r = 0.83 and MAE = 0.83. Using at-home data, DFBIA was strongly associated with absolute muscle force of participants (n = 198, p < 0.001).

CONCLUSION

These results demonstrate the utility of wearable DFBIA for non-invasively estimating muscle force and pain through the changes in intramuscular fluid dynamics.

SIGNIFICANCE

The presented approach may inform development of future wearable systems for quantifying muscle health and provide a novel framework for athletic performance optimization and injury prevention.

Validating Adhesive-Free Bioimpedance of the Leg in Mid-Activity and Uncontrolled Settings

OBJECTIVE

Musculoskeletal health monitoring is limited in everyday settings where patient symptoms can substantially change - delaying treatment and worsening patient outcomes. Wearable technologies aim to quantify musculoskeletal health outside clinical settings but sensor constraints limit usability. Wearable localized multi-frequency bioimpedance assessment (MFBIA) shows promise for tracking musculoskeletal health but relies on gel electrodes, hindering extended at-home use. Here, we address this need for usable technologies for at-home musculoskeletal health assessment by designing a wearable adhesive-free MFBIA system using textile electrodes in extended uncontrolled mid-activity settings.

METHODS

An adhesive-free multimodal wearable leg MFBIA system was developed in-lab under realistic conditions (5 participants, 45 measurements). Mid-activity textile and gel electrode MFBIA was compared across multiple compound movements (10 participants). Accuracy in tracking long-term changes in leg MFBIA was assessed by correlating gel and textile MFBIA simultaneously recorded in uncontrolled settings (10 participants, 80+ measurement hours).

RESULTS

Mid-activity MFBIA measurements with textile electrodes agreed highly with (ground truth) gel electrode measurements (average [Formula: see text], featuring <1-Ohm differences (0.618 ± 0.340 Ω) across all movements. Longitudinal MFBIA changes were successfully measured in extended at-home settings (repeated measures r = 0.84). Participant responses found the system to be comfortable and intuitive (8.3/10), and all participants were able to don and operate the system independently.

CONCLUSION

This work demonstrates wearable textile electrodes can be a viable substitute for gel electrodes when monitoring leg MFBIA in dynamic, uncontrolled settings.

SIGNIFICANCE

Adhesive-free MFBIA can improve healthcare by enabling robust wearable musculoskeletal health monitoring in at-home and everyday settings.

A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware

A novel method for embedded hardware-based parameter estimation of the Cole model of bioimpedance is developed and presented. The model parameters R_∞, R₁ and C are estimated using the derived set of equations based on measured values of real (R) and imaginary part (X) of bioimpedance, as well as the numerical approximation of the first derivative of quotient R/X with respect to angular frequency. The optimal value for parameter α is estimated using a brute force method. The estimation accuracy of the proposed method is very similar with the relevant work from the existing literature. Moreover, performance evaluation was performed using the MATLAB software installed on a laptop, as well as on the three embedded-hardware platforms (Arduino Mega2560, Raspberry Pi Pico and XIAO SAMD21). Obtained results showed that the used platforms can perform reliable bioimpedance processing with the same accuracy, while Raspberry Pi Pico is the fastest solution with the smallest energy consumption.

Localized Multi-Site Knee Bioimpedance as a Predictor for Knee Osteoarthritis Associated Pain Within Older Adults During Free-Living

The drastic increase in the aging population has increased the prevalence of osteoarthritis in the United States. The ability to monitor symptoms of osteoarthritis (such as pain) within a free-living environment could improve understanding of each person's experiences with this disease and provide opportunities to personalize treatments specific to each person and their experience. In this work, localized knee tissue bioimpedance and self-reports of knee pain were collected from older adults ([Formula: see text]) with and without knee osteoarthritis over 7 days of free-living to evaluate if knee tissue bioimpedance is associated with persons' knee pain experience. Within the group of persons' with knee osteoarthritis increases in 128 kHz per-length resistance and decreases in 40 kHz per-length reactance were associated with increased probability of persons having active knee pain ([Formula: see text] and [Formula: see text]).

A review of bio-impedance devices

Bio-impedance measurement analysis primarily refers to a safe and a non-invasive technique to analyze the electrical changes in living tissues on the application of low-value alternating current. It finds applications both in the biomedical and the agricultural fields. This paper concisely reviews the origin and measurement approaches for concepts and fundamentals of bio-impedance followed by a critical review on bio-impedance portable devices with main emphasis on the embedded system approach which is in demand due to its miniature size and present lifestyle preference of monitoring health in real time. The paper also provides a comprehensive review of various bio-impedance circuits with emphasis on the measurement and calibration techniques.

Design and Manufacturing of Equipment for Investigation of Low Frequency Bioimpedance

The purpose of this study was to highlight a method of making equipment for the investigation of low frequency bioimpedance. A constant current with an average value of I = 100 µA is injected into the human body via means of current injection electrodes, and the biological signal is taken from the electrodes of electric potential charged with the biopotentials generated by the human body. The resulting voltage, ΔU is processed by the electronic conditioning system. The mathematical model of the four-electrode system in contact with the skin, and considering a target organ, was simplified to a single equivalent impedance. The capacitive filter low passes down from the differential input of the first instrumentation amplifier together with the isolated capacitive barrier integrated in the precision isolated secondary amplifier and maintains the biological signal taken from the electrodes charged with the undistorted biopotentials generated by the human body. Mass loops are avoided, and any electric shocks or electrostatic discharges are prevented. In addition, for small amplitudes of the biological signal, electromagnetic interferences of below 100 Hz of the power supply network were eliminated by using an active fourth-order Bessel filtering module. The measurements performed for the low frequency of f = 100 Hz on the volunteers showed for the investigated organs that the bioelectrical resistivities vary from 90 Ωcm up to 450 Ωcm, and that these are in agreement with other published and disseminated results for each body zone.

Bioimpedance Measurement of Knee Injuries Using Bipolar Electrode Configuration

Currently, there is no suitable solution for the point-of-care diagnosis of knee injuries. A potential portable and low-cost technique for accessing and monitoring knee injuries is bioimpedance measurement. This study validated the feasibility of the bipolar electrode configuration for knee bioimpedance measurement with two electrodes placed on a fixed pair of knee acupuncture locations called Xiyan. Then, the study collected 76 valid samples to investigate the relationship between bioimpedance and knee injuries, among whom 39 patients have unilateral knee injuries, and 37 individuals have healthy knees. The self-contrast results indicated that knee injuries caused a reduction of bioimpedance of the knee by about 5% on average, which was detectable at around 100 kHz (p ≈ 0.001). Furthermore, the results analyzed by principal component analysis and support vector machines show that the detection sensitivity can reach 87.18% using the leave-one-out cross-validation. We also proposed a low-cost and portable bioimpedance measurement device that meets the needs for measuring knee joint bioimpedance.

On-Chip Sinusoidal Signal Generators for Electrical Impedance Spectroscopy: Methodological Review

This paper reviews architectures and circuit implementations of on-chip sinusoidal signal generators (SSGs) for electrical impedance spectroscopy (EIS) applications. In recent years, there have been increasing interests in on-chip EIS systems, which measure a target material's impedance spectrum over a frequency range. The on-chip implementation allows EIS systems to have low power and small form factor, enabling various biomedical applications. One of the key building blocks of on-chip EIS systems is on-chip SSG, which determines the frequency range and the analysis precision of the whole EIS system. On-chip SSGs are generally required to have high linearity, wide frequency range, and high power and area efficiency. They are typically composed of three stages in general: waveform generation, linearity enhancement, and current injection. First, a sinusoidal waveform should be generated in SSGs. The generated waveform's frequency should be accurately adjustable over a wide range. The firstly generated waveform may not be perfectly linear, including unwanted harmonics. In the following linearity-enhancement step, these harmonics are attenuated by using filters typically. As the linearity of the waveform is improved, the precision of the EIS system gets ensured. Lastly, the filtered voltage waveform is now converted to a current by a current driver. Then, the current sinusoidal signal is injected into the target impedance. This review discusses the principles, advantages, and disadvantages of various techniques applied to each step in state-of-the-art on-chip SSGs. In addition, state-of-the-art designs are compared and summarized.

System Performance and User Feedback Regarding Wearable Bioimpedance System for Multi-Site Knee Tissue Monitoring: Free-Living Pilot Study With Healthy Adults

Knee-focused wearable devices have the potential to support personalized rehabilitation therapies by monitoring localized tissue alterations related to activities that reduce functional symptoms and pain. However, supporting these applications requires reported data to be reliable and accurate which can be challenging in the unsupervised free-living conditions that wearable devices are deployed. This pilot study has assessed a knee-focused wearable sensor system to quantify 1) system performance (operation, rates of data artifacts, environment impacts) to estimate realistic targets for reliable data with this system and 2) user experiences (comfort, fit, usability) to help inform future designs to increase usability and adoption of knee-focused wearables. Study data was collected from five healthy adult participants over 2 days, with 84.5 and 35.9% of artifact free data for longitudinal and transverse electrode configurations. Small to moderate positive correlations were also identified between changes in resistance, temperature, and humidity with respect to acceleration to highlight how this system can be used to explore relationships between knee tissues and environmental/activity context.

A low-cost, portable, two-dimensional bioimpedance distribution estimation system based on the AD5933 impedance converter

This study proposes a low-cost, portable, eight-channel electrical impedance tomograph based on the AD5933 impedance converter. The patterns for current injection and voltage measurement are managed by an Arduino Mega 2560 board and four 74HC4067 Texas Instruments multiplexers. Regarding the experimental results, the errors in the impedance estimates of an electrical circuit that represents a Cole model were less than 1.14% for the magnitude and 4.15% for the phase. Furthermore, the signal-to-noise ratio measured in a resistive phantom was 55.23 dB. Additional experiments consisted of placing five spheres of different size and conductivity in a saline tank, measuring their impedance through eight electrodes, and then generating impedance maps using the Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EIDORS). These maps were different for each sphere, suggesting the proposed prototype as a promising alternative for medical applications.

Evaluating Research Grade Bioimpedance Hardware Using Textile Electrodes for Long-Term Fluid Status Monitoring

Fluid overload is a chronic medical condition that affects over six million Americans with conditions such as congestive heart failure, end-stage renal disease, and lymphedema. Remote management of fluid overload continues to be a leading clinical challenge. Bioimpedance is one technique that can be used to estimate the hydration of tissue and track it over time. However, commercially available bioimpedance measurement systems are bulky, expensive, and rely on Ag/AgCl electrodes that dry out and can irritate the skin. The use of bioimpedance today is therefore limited to clinical and research settings, with measurements performed at daily intervals or over short periods of time rather than continuously and long-term. This paper proposes using wearable calf bioimpedance measurements integrated into a compression sock for long-term fluid overload management. A PCB was developed using standard measurement techniques that measures the calf bioimpedance using a custom analog front-end built around an AD8302 gain-phase detection chip. Data is transmitted wirelessly via Bluetooth Low Energy to an iOS device using a custom iOS app. Bioimpedance data were collected both from the wearable system and a commercial measurement system (ImpediMed SFB7) using RRC networks, Ag/AgCl electrodes, and the textile compression sock. Bioimpedance data collected from the wearable system showed close agreement with data from the SFB7 when using RRC networks and in five healthy human subjects with Ag/AgCl electrodes. However, when using the textile compression sock the wearable system had worse precision than the SFB7 (4% run to run compared to <1% run to run) and there were larger differences between the two systems than when using the RRC networks and the Ag/AgCl electrodes. Wearable system precision and agreement with the SFB7 was improved by pressure or light wetting of the current electrodes on the sock. Future research should focus on reliable elimination of low-frequency artifacts in research grade hardware to enable long-term calf bioimpedance measurements for fluid overload management.

A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee

A personalized model of the human knee for enhancing the inter-individual reproducibility of a measurement method for monitoring Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) after transdermal delivery is proposed. The model is based on the solution of Maxwell Equations in the electric-quasi-stationary limit via Finite Element Analysis. The dimensions of the custom geometry are estimated on the basis of knee circumference at the patella, body mass index, and sex of each individual. An optimization algorithm allows to find out the electrical parameters of each subject by experimental impedance spectroscopy data. Muscular tissues were characterized anisotropically, by extracting Cole-Cole equation parameters from experimental data acquired with twofold excitation, both transversal and parallel to tissue fibers. A sensitivity and optimization analysis aiming at reducing computational burden in model customization achieved a worst-case reconstruction error lower than 5%. The personalized knee model and the optimization algorithm were validated in vivo by an experimental campaign on thirty volunteers, 67% healthy and 33% affected by knee osteoarthritis (Kellgren-Lawrence grade ranging in [1,4]), with an average error of 3%.

Flexible PCB Failures From Dynamic Activity and Their Impacts on Bioimpedance Measurements: A Wearable Case Study

Wearable health monitoring systems that collect data in free-living environments are becoming increasingly popular. Flexible printed circuits provide a commercially available option that can conform to the shape of a wearable system and support electronic sensing and flexible interconnect. However, repetitive dynamic activity can stress and damage the interconnect of flexible PCBs which degrades data quality. This case study evaluated the performance of flexible PCBs providing interconnect between electrodes and sensing electronics for tissue bioimpedance measurements in a wearable system. Resistance data (1 kHz to 128 kHz) was collected from localized knee tissues of 3 participants using the wearable design with flexible PCBs over 7 days of free-living. From electrical and optical inspection after use trace cracking of the flexible PCBs occurred, degrading tissue resistances reported by the wearable system. Exploration of these results advances understanding of how flexible PCBs perform in free-living conditions for wearable bioimpedance applications.

An Integrated Multimodal Knee Brace Enabling Mid-Activity Tracking for Joint Health Assessment

Developments in wearable technologies created opportunities for non-invasive joint health assessment while subjects perform daily activities during rehabilitation and recovery. However, existing state-of-art solutions still require a health professional or a researcher to set up the device, and most of them are not convenient for at-home use. In this paper, we demonstrate the latest version of the multimodal knee brace that our lab previously developed. This knee brace utilizes four sensing modalities: joint acoustic emissions (JAEs), electrical bioimpedance (EBI), activity and temperature. We designed custom printed-circuit boards and developed firmware to acquire high quality data. For the brace material, we used a commercial knee brace and modified it for the comfort of patients as well as to secure all electrical connections. We updated the electronics to enable rapid EBI measurements for mid-activity tracking. The performance of the multimodal knee brace was evaluated through a proof-of-concept human subjects study (n=9) with 2 days of measurement and 3 sessions per day. We obtained consistent EBI data with less than 1 Ω variance in measured impedance within six full frequency sweeps (each sweep is from 5 kHz to 100 kHz with 256 frequency steps) from each subject. Then, we asked subjects to perform 10 unloaded knee flexion/extensions, while we measured continuous 5 kHz and 100 kHz EBI at every 100 ms. The ratio of the range of reactance (ΔX_5kHz/ΔX100kHz) was found to be less than 1 for all subjects for all cycles, which indicates lack of swelling and thereby a healthy joint. We also conducted intra and inter session reliability analysis for JAE recordings through intraclass correlation analysis (ICC), and obtained excellent ICC values (>0.75), suggesting reliable performance on JAE measurements. The presented knee brace could readily be used at home in future work for knee health monitoring of patients undergoing rehabilitation or recovery.

Localized Bioimpedance Measurements with the MAX3000x Integrated Circuit: Characterization and Demonstration

The commercial availability of integrated circuits with bioimpedance sensing functionality is advancing the opportunity for practical wearable systems that monitor the electrical impedance properties of tissues to identify physiological features in support of health-focused applications. This technical note characterizes the performance of the MAX3000x (resistance/reactance accuracy, power modes, filtering, gains) and is available for on-board processing (electrode detection) for localized bioimpedance measurements. Measurements of discrete impedances that are representative of localized tissue bioimpedance support that this IC has a relative error of <10% for the resistance component of complex impedance measurements, but can also measure relative alterations in the 250 mΩ range. The application of the MAX3000x for monitoring localized bicep tissues during activity is presented to highlight its functionality, as well as its limitations, for multi-frequency measurements. This device is a very-small-form-factor single-chip solution for measuring multi-frequency bioimpedance with significant on-board processing with potential for wearable applications.

Knee Acoustic Emissions as a Digital Biomarker of Disease Status in Juvenile Idiopathic Arthritis

In this paper, we quantify the joint acoustic emissions (JAEs) from the knees of children with juvenile idiopathic arthritis (JIA) and support their use as a novel biomarker of the disease. JIA is the most common rheumatic disease of childhood; it has a highly variable presentation, and few reliable biomarkers which makes diagnosis and personalization of care difficult. The knee is the most commonly affected joint with hallmark synovitis and inflammation that can extend to damage the underlying cartilage and bone. During movement of the knee, internal friction creates JAEs that can be non-invasively measured. We hypothesize that these JAEs contain clinically relevant information that could be used for the diagnosis and personalization of treatment of JIA. In this study, we record and compare the JAEs from 25 patients with JIA-10 of whom were recorded a second time 3-6 months later-and 18 healthy age- and sex-matched controls. We compute signal features from each of those record cycles of flexion/extension and train a logistic regression classification model. The model classified each cycle as having JIA or being healthy with 84.4% accuracy using leave-one-subject-out cross validation (LOSO-CV). When assessing the full JAE recording of a subject (which contained at least 8 cycles of flexion/extension), a majority vote of the cycle labels accurately classified the subjects as having JIA or being healthy 100% of the time. Using the output probabilities of a JIA class as a basis for a joint health score and test it on the follow-up patient recordings. In all 10 of our 6-week follow-up recordings, the score accurately tracked with successful treatment of the condition. Our proposed JAE-based classification model of JIA presents a compelling case for incorporating this novel joint health assessment technique into the clinical work-up and monitoring of JIA.

Band Electrodes Reduce Simulated Calf Bioimpedance Measurement Errors Due to Muscle Anisotropy

Remote monitoring of fluid status via calf bioimpedance measurements could improve the experience of patients with congestive heart failure and reduce readmission rates. Most measurements today use conventional Ag/AgCl electrodes and a short inter-electrode spacing, resulting in current flowing primarily near the electrodes, preventing deeper current penetration and in turn accurate volume estimation. Textile band electrodes may more evenly distribute current throughout the calf. In the present study, simulations were conducted to investigate the impact of inter-electrode spacing/placement and fat tissue on bioimpedance using both Ag/AgCl electrodes and textile band electrodes. Simulation results showed that increasing the inter-electrode spacing can improve current distribution in the tissue, but there are still errors that increase with fat thickness (14.3% error at 10 cm spacing down to 1.7% error at 20 cm spacing for a "nominal" fat thickness, vs. -0.3% and -0.5% error for band electrodes). Band electrodes most closely matched the expected resistance and seem the most suitable regardless of inter-electrode spacing.

Wearable bioimpedance for continuous and context-aware clinical monitoring

Bioimpedance monitoring provides a non-invasive, safe and affordable opportunity to monitor total body water for a wide range of clinical applications. However, the measurement is susceptible to variations in posture and movement. Existing devices do not account for these variations and are therefore unsuitable to perform continuous measurements to depict trend changes. We developed a wearable bioimpedance monitoring system with embedded real-time posture detection using a distributed accelerometer network. We tested the device on 14 healthy volunteers following a standardized protocol of posture change and evaluated the agreement with a commercial device. The impedance showed a high correlation (r>0.98), a bias of -4.5 Ω, and limits of agreement of -30 and 21 Ω. Context-awareness was achieved with an accuracy of 94.6% by classifying data from two accelerometers placed at the upper and lower leg. The calculated current consumption of the system was as low as 10 mA during continuous measurement operation, suggesting that the system can be used for continuous measurements over multiple days without charging. The proposed motion-aware design will enable the measurement of relevant bioimpedance parameters over long periods and support informed clinical decision making.

Smart Bioimpedance Spectroscopy Device for Body Composition Estimation

The purpose of this work is to describe a first approach to a smart bioimpedance spectroscopy device for its application to the estimation of body composition. The proposed device is capable of carrying out bioimpedance measurements in multiple configurable frequencies, processing the data to obtain the modulus and the bioimpedance phase in each of the frequencies, and transmitting the processed information wirelessly. Another novelty of this work is a new algorithm for the identification of Cole model parameters, which is the basis of body composition estimation through bioimpedance spectroscopy analysis. Against other proposals, the main advantages of the proposed method are its robustness against parasitic effects by employing an extended version of Cole model with phase delay and three dispersions, its simplicity and low computational load. The results obtained in a validation study with respiratory patients show the accuracy and feasibility of the proposed technology for bioimpedance measurements. The precision and validity of the algorithm was also proven in a validation study with peritoneal dialysis patients. The proposed method was the most accurate compared with other existing algorithms. Moreover, in those cases affected by parasitic effects the proposed algorithm provided better approximations to the bioimpedance values than a reference device.

Textile band electrodes as an alternative to spot Ag/AgCl electrodes for calf bioimpedance measurements

OBJECTIVE

To evaluate the performance of five different types of textiles as band electrodes for calf bioimpedance measurements in comparison with conventional spot Ag/AgCl electrodes.

APPROACH

Calf bioimpedance measurements were performed in 10 healthy volunteers with five different textile materials cut into bands and Ag/AgCl spot electrodes as a baseline. Collected bioimpedance data were analyzed in terms of precision, fit error and presence of measurement artifacts. Each textile material was also evaluated for participant comfort.

MAIN RESULTS

Bioimpedance values for spot electrodes were higher at low frequencies as compared with band electrodes but not at high frequencies. This suggests that spot electrodes have frequency dependent current distributions that adversely impact their use for volume measurements and band electrodes are preferable. The SMP130T-B fabric had the highest precision and the lowest best fit error to the Cole model of the tested textile materials. However, it was the least comfortable textile and most expensive. The Stretch material performed slightly worse than the SMP130T-B fabric, but was half the cost and the most comfortable.

SIGNIFICANCE

These results suggest that there are suitable textile materials for use as dry, band electrodes for calf bioimpedance measurements and that these band electrodes enable greater current uniformity. These textiles could be integrated into a compression sock for remote monitoring of diseases such as Congestive Heart Failure.

Robust Longitudinal Ankle Edema Assessment Using Wearable Bioimpedance Spectroscopy

OBJECTIVE

We present a robust methodology for tracking ankle edema longitudinally based on bioimpedance spectroscopy (BIS).

METHODS

We designed a miniaturized BIS measurement system and employed a novel calibration method that enables accurate, high-resolution measurements with substantially lower power consumption than conventional approaches. Using this state-of-the-art wearable BIS measurement system, we developed a differential measurement technique for robust assessment of ankle edema. This technique addresses many of the major challenges in longitudinal BIS-based edema assessment, including day-to-day variability in electrode placement, positional/postural variability, and intersubject variability.

RESULTS

We first evaluated the hardware in bench-top testing, and determined the error of the bioimpedance measurements to be 0.4 Ω for the real components and 0.54 Ω for the imaginary components with a resolution of 0.2 Ω. We then validated the hardware and differential measurement technique in: 1) an ex vivo, fresh-frozen, cadaveric limb model, and 2) a cohort of 11 human subjects for proof of concept (eight healthy controls and five subjects with recently acquired acute unilateral ankle injury).

CONCLUSION

The hardware design, with novel calibration methodology, and differential measurement technique can potentially enable long-term quantification of ankle edema throughout the course of rehabilitation following acute ankle injuries.

SIGNIFICANCE

This could lead to better-informed decision making regarding readiness to return to activities and/or tailoring of rehabilitation activities to an individual's changing needs.

Quantifying the Effects of Increasing Mechanical Stress on Knee Acoustical Emissions Using Unsupervised Graph Mining

In this paper, we investigate the effects of increasing mechanical stress on the knee joints by recording knee acoustical emissions and analyze them using an unsupervised graph mining algorithm. We placed miniature contact microphones on four different locations: on the lateral and medial sides of the patella and superficial to the lateral and medial meniscus. We extracted audio features in both time and frequency domains from the acoustical signals and calculated the graph community factor (GCF): an index of heterogeneity (variation) in the sounds due to different loading conditions enforced on the knee. To determine the GCF, a k-nearest neighbor graph was constructed and an Infomap community detection algorithm was used to extract all potential clusters within the graph-the number of detected communities were then quantified with GCF. Measurements from 12 healthy subjects showed that the GCF increased monotonically and significantly with vertical loading forces (mean GCF for no load = 30 and mean GCF for maximum load [body weight] = 39). This suggests that the increased complexity of the emitted sounds is related to the increased forces on the joint. In addition, microphones placed on the medial side of the patella and superficial to the lateral meniscus produced the most variation in the joint sounds. This information can be used to determine the optimal location for the microphones to obtain acoustical emissions with greatest sensitivity to loading. In future work, joint loading quantification based on acoustical emissions and derived GCF can be used for assessing cumulative knee usage and loading during activities, for example for patients rehabilitating knee injuries.

Using Knee Acoustical Emissions for Sensing Joint Health in Patients with Juvenile Idiopathic Arthritis: A Pilot Study

In this paper, we present a pilot study evaluating novel methods for assessing joint health in patients with Juvenile Idiopathic Arthritis (JIA) using wearable acoustical emission measurements from the knees. Measurements were taken from four control subjects with no known knee injuries, and from four subjects with JIA, before and after treatment. Time and frequency domain features were extracted from the acoustical emission signals and used to compute a knee audio score. The score was used to separate out the two groups of subjects based solely on the sounds their joints produce. It was created using a soft classifier based on gradient boosting trees. The knee audio scores ranged from 0-1 with 0 being a healthy knee and 1 being an involved joint with arthritis. Leave-one-subject-out cross-validation (LOSO-CV) was used to validate the algorithm. The average of the right and left knee audio scores was 0.085±0.099 and 0.89±0.012 for the control group and group with JIA, respectively (p<0.05). The average knee audio score for the subjects with JIA decreased from 0.89±0.012 to 0.25±0.20 following successful treatment (p<0.05). The knee audio score metric successfully distinguished between the control subjects and subjects with JIA. The scores calculated before and after treatment accurately reflected the observed clinical course of the subjects with JIA. After successful treatment, the subjects with JIA were classified as healthy by the algorithm. Knee acoustical emissions provide a novel and cost-effective method for monitoring JIA, and can be used as an objective guide for assessing treatment efficacy.

Fatigue-Induced Cole Electrical Impedance Model Changes of Biceps Tissue Bioimpedance

Bioimpedance, or the electrical impedance of biological tissues, describes the passive electrical properties of these materials. To simplify bioimpedance datasets, fractional-order equivalent circuit presentations are often used, with the Cole-impedance model being one of the most widely used fractional-order circuits for this purpose. In this work, bioimpedance measurements from 10 kHz to 100 kHz were collected from participants biceps tissues immediately prior and immediately post completion of a fatiguing exercise protocol. The Cole-impedance parameters that best fit these datasets were determined using numerical optimization procedures, with relative errors of within approximately ± 0.5 % and ± 2 % for the simulated resistance and reactance compared to the experimental data. Comparison between the pre and post fatigue Cole-impedance parameters shows that the R ∞ , R 1 , and f p components exhibited statistically significant mean differences as a result of the fatigue induced changes in the study participants.

Toward Non-Invasive and Automatic Intravenous Infiltration Detection: Evaluation of Bioimpedance and Skin Strain in a Pig Model

Intravenous (IV) therapy is prevalent in hospital settings, where fluids are typically delivered with an IV into a peripheral vein of the patient. IV infiltration is the inadvertent delivery of fluids into the extravascular space rather than into the vein (and requires urgent treatment to avoid scarring and severe tissue damage), for which medical staff currently needs to check patients periodically. In this paper, the performance of two non-invasive sensing modalities, electrical bioimpedance (EBI), and skin strain sensing, for the automatic detection of IV infiltration was investigated in an animal model. Infiltrations were physically simulated on the hind limb of anesthetized pigs, where the sensors for EBI and skin strain sensing were co-located. The obtained data were used to examine the ability to distinguish between infusion into the vein and an infiltration event using bioresistance and bioreactance (derived from EBI), as well as skin strain. Skin strain and bioresistance sensing could achieve detection rates greater than 0.9 for infiltration fluid volumes of 2 and 10 mL, respectively, for a given false positive, i.e., false alarm rate of 0.05. Furthermore, the fusion of multiple sensing modalities could achieve a detection rate of 0.97 with a false alarm rate of 0.096 for 5mL fluid volume of infiltration. EBI and skin strain sensing can enable non-invasive and real-time IV infiltration detection systems. Fusion of multiple sensing modalities can help to detect expanded range of leaking fluid volumes. The provided performance results and comparisons in this paper are an important step towards clinical translation of sensing technologies for detecting IV infiltration.

Universal Pre-Ejection Period Estimation Using Seismocardiography: Quantifying the Effects of Sensor Placement and Regression Algorithms

Seismocardiography (SCG), the measurement of local chest vibrations due to the heart and blood movement, is a non-invasive technique to assess cardiac contractility via systolic time intervals such as the pre-ejection period (PEP). Recent studies show that SCG signals measured before and after exercise can effectively classify compensated and decompensated heart failure (HF) patients through PEP estimation. However, the morphology of the SCG signal varies from person to person and sensor placement making it difficult to automatically estimate PEP from SCG and electrocardiogram signals using a global model. In this proof-of-concept study, we address this problem by extracting a set of timing features from SCG signals measured from multiple positions on the upper body. We then test global regression models that combine all the detected features to identify the most accurate model for PEP estimation obtained from the best performing regressor and the best sensor location or combination of locations. Our results show that ensemble regression using XGBoost with a combination of sensors placed on the sternum and below the left clavicle provide the best RMSE = 11.6 ± 0.4 ms across all subjects. We also show that placing the sensor below the left or right clavicle rather than the conventional placement on the sternum results in more accurate PEP estimates.

Wearable knee health system employing novel physiological biomarkers

Knee injuries and chronic disorders, such as arthritis, affect millions of Americans, leading to missed workdays and reduced quality of life. Currently, after an initial diagnosis, there are few quantitative technologies available to provide sensitive subclinical feedback to patients regarding improvements or setbacks to their knee health status; instead, most assessments are qualitative, relying on patient-reported symptoms, performance during functional tests, and physical examinations. Recent advances have been made with wearable technologies for assessing the health status of the knee (and potentially other joints) with the goal of facilitating personalized rehabilitation of injuries and care for chronic conditions. This review describes our progress in developing wearable sensing technologies that enable quantitative physiological measurements and interpretation of knee health status. Our sensing system enables longitudinal quantitative measurements of knee sounds, swelling, and activity context during clinical and field situations. Importantly, we leverage machine-learning algorithms to fuse the low-level signal and feature data of the measured time series waveforms into higher level metrics of joint health. This paper summarizes the engineering validation, baseline physiological experiments, and human subject studies-both cross-sectional and longitudinal-that demonstrate the efficacy of using such systems for robust knee joint health assessment. We envision our sensor system complementing and advancing present-day practices to reduce joint reinjury risk, to optimize rehabilitation recovery time for a quicker return to activity, and to reduce health care costs.