Instrumented Shoe Research Articles

Stair-Fall Risk Parameters in a Controlled Gait Laboratory Environment and Real (Domestic) Houses: A Prospective Study in Faller and Non-Faller Groups.

Falling on stairs is a major health hazard for older people. Risk factors for stair falls have been identified, but these are mostly examined in controlled biomechanics/gait laboratory environments, on experimental stairs with a given set of step dimensions. It remains unknown whether the conclusions drawn from these controlled environments would apply to the negotiation of other domestic staircases with different dimensions in real houses where people live. The aim of this paper is to investigate whether selected biomechanical stepping behavior determined through stair gait parameters such as foot clearance, foot contact length and cadence are maintained when the staircase dimensions are different in real houses. Twenty-five older adults (>65 years) walked on a custom-made seven-step laboratory staircase. Older adults were classified into two groups (fallers and non-fallers) based on recent fall history. Among the 25 participants, 13 people had at least one fall, trip, or slip in the last six months and they were assigned to the fallers group; 12 people did not experience any fall in the last six months, so they were assigned to the non-fallers group. In addition, these participants walked on the stairs in three different real exemplar houses wearing a novel instrumented shoe sensor system that could measure the above stair gait parameters. MATLAB was used to extract fall risk parameters from the collected data. One-way ANOVA was used to compare fall risk parameters on the different staircases. In addition, the laboratory-based fall risk parameters were compared to those derived from the real house stairs. There was a significant difference in selected stair-fall biomechanical risk factors among the house and laboratory staircases. The fall risk group comparisons suggest that high-risk fallers implemented a biomechanically riskier strategy that could increase overall falling risk. The significant differences due to the main effects of the fallers and non-fallers groups were obtained. For example, when ascending, the fallers group had less foot clearance on the entry (p = 0.016) and middle steps (p = 0.003); in addition, they had more foot clearance variability on the entry steps (p = 0.003). This suggests that the fallers group in this present study did not adopt more conservative stepping strategies during stair ascent compared to low-risk older adults. By showing less foot clearance and more variability in foot clearance, the risk for a trip would be increased.

A Novel Kinematic Gait Parameter-Based Vibrotactile Cue for Freezing of Gait Mitigation among Parkinson's Patients: A Pilot Study.

Auditory and visual cues have been efficacious in laboratory-based freezing of gait (FoG) mitigation in Parkinson's disease (PD). However, real-life applications of these cues are restricted due to inconvenience to the users. Closed-loop vibrotactile cues based on temporal gait events have overcome the shortcomings of auditory and visual cueing. However, kinematic gait parameter-driven vibrotactile cueing has not been explored yet. Kinematic gait parameter-driven cueing is more effective than temporal cueing, according to FoG pathophysiology studies. Therefore, we developed and pilot-tested a novel cueing scheme in which the foot-to-ground angle at heel strike (FGA_HS) is estimated using indigenous instrumented shoes to drive vibrotactile cueing. Ten PD freezers underwent a 6-meter timed walk test in the off-medication state with and without the cue and after medication without the cue. The proposed system potentially mitigated FoG, quantified by a reduction in the ratio of time spent freezing to the total walking time and the number of FoGs. The FoG mitigation potential of the cue was further supported by increased anteroposterior center of pressure progression and FGA_HS. With a future comprehensive validation in a larger number of participants, the novel cue could likely be used in practice and commercialized.

A Low-Cost Instrumented Shoe System for Gait Phase Detection Based on Foot Plantar Pressure Data

A Low-Cost Instrumented Shoe System for Gait Phase Detection Based on Foot Plantar Pressure Data

Slip Risk Prediction Using Intelligent Insoles and a Slip Simulator

Slip and fall accidents are the leading cause of injuries for all ages, and for fatal injuries in adults over 65 years. Various factors, such as floor surface conditions and contaminants, shoe tread patterns, and gait behavior, affect the slip risk. Moreover, the friction between the shoe outsoles and the floor continuously changes as their surfaces undergo normal wear over time. However, continuous assessment of slip resistance is very challenging with conventional measurement techniques. This study addresses this challenge by introducing a novel approach that combines sensor fusion technology and machine learning techniques to create intelligent insoles designed for fall risk prediction. In addition, a state-of-the-art slip simulator, capable of mimicking the foot’s motion during a slip, was developed and utilized for the assessment of slipperiness between various shoes and floor surfaces. Data acquisition involved the collection of pressure data and three-axial accelerations using instrumented shoe insoles, complemented by friction coefficient measurements via the slip simulator. The collected dataset includes four types of shoes, three floor surfaces, and four surface conditions, including dry, wet, soapy, and oily. After preprocessing of the collected dataset, the simulator was used to train five different machine learning algorithms for slip risk classification. The trained algorithms provided promising results for slip risk prediction for different conditions, offering the potential to be employed in real-time slip risk prediction and safety enhancement.

A Performance Evaluation of Overground Gait Training With a Mobile Body Weight Support System Using Wearable Sensors

Overground gait training under body weight support (BWS) for patients who suffer from neurological injuries has been proven practical in recovering from walking ability. Conventionally, skilled therapists or additional robots are required to assist the patient’s body weight and pelvis movement, making the rehabilitation process physically and economically burdensome. We investigate if a BWS walker using only two actuators can support the user’s body weight and simultaneously protect/assist the transverse pelvis rotation, improving natural gait with minimal motion compensation. In this paper, a BWS strategy called transverse pelvis rotation support (TPRS) is proposed to enable the BWS system to generate cable tension in the forward direction, as a purpose to support transverse pelvis rotation in addition to our previously proposed static or variable BWS. Wearable sensory devices, including instrumented shoes and harness, were developed to provide real-time ground reaction force and pelvis rotation signals simultaneously. Ten non-disabled participants were unloaded with 0% ~ 15% BWS under four different controls. Vertical ground reaction force, transverse pelvis kinematics, and user experience were compared using proposed controls. One-Way repeated measures ANOVA analysis assessed if control strategies generally affect the performance. All proposed controls enable the walker to support part of the user’s body weight. SBWS-TPRS and VBWS-TPRS control enable users to achieve a significantly improved pelvic motion and prolonged single support phase than pure static BWS or variable BWS, although users perceive a higher workload under them. The proposed BWS controls show the potential to become a complementary method in gait rehabilitation.

Remotely delivered, individualized, and self-directed gait modification for knee osteoarthritis: A pilot trial

BackgroundGait modification interventions have reported variable results and relied on in-person biofeedback limiting clinical accessibility. Our objective was to assess a remotely delivered and self-directed gait modification for knee osteoarthritis. MethodsThis was an unblinded, 2-arm, delayed control, randomized pilot trial (NCT04683913). Adults aged ≥50 years with symptomatic medial knee osteoarthritis were randomized to an immediate group (Week 0: Baseline, Intervention; Week 6: Follow-up, Week 10: Retention) or delayed group (Week 0: Baseline, Wait Period, Week 6: Secondary Baseline, Intervention, Week 12: Follow-up, Week 16: Retention). Participants practiced modifying their foot progression angle “as much as was comfortable” while receiving support via weekly telerehabilitation appointments and remote monitoring with an instrumented shoe. Primary outcomes included participation, foot progression angle modification magnitude, confidence, difficulty, and satisfaction while secondary outcomes included symptoms and knee biomechanics during gait. ResultsWe screened 134 people and randomized 20. There was no loss to follow up and 100% attendance at the telerehabilitation appointments. By follow up, participants reported high confidence (8.6/10), low difficulty (2.0/10), and satisfaction (75%) with the intervention and no significant adverse events. Foot progression angle was modified by 11.4° ± 5.6, which was significantly different (p < 0.001, η2g = 0.8) when compared between groups. No other between-group differences were significant, while several significant pre-post improvements in pain (d = 0.6, p = 0.006) and knee moments (d = 0.6, p = 0.01) were observed. InterpretationA personalized, self-directed gait modification supported with telerehabilitation is feasible, and the preliminary effects on symptoms and biomechanics align with past trials. A larger trial is warranted to evaluate efficacy.

Design of SmartWalk for Estimating Implication of Pathway With Turn and Task Condition on Postural and Gait Indices: Relevance to Fear of Fall.

Fear of Fall (FoF) is often associated with postural and gait abnormalities leading to decreased mobility in individuals with Parkinson's Disease (PD). The variability in knee flexion (postural index) during heel-strike and toe-off events while walking can be related to one's FoF. Depending on the progression of the disease, gait abnormality can be manifested as start/turn/stop hesitation, etc. adversely affecting one's cadence along with an inability to transfer weight from one leg to the other. Also, task demands can have implications on one's gait and posture. Given that individuals with PD often suffer from FoF and their dynamic balance is affected by task conditions and pathways, in- depth investigation is warranted to understand the implications of task condition and pathways on one's gait and posture. This necessitates use of portable, wearable device that can capture one's gait-related indices and knee flexion in free-living conditions. Here, we have designed a portable, wearable and cost-effective device (SmartWalk) comprising of instrumented Shoes integrated with knee flexion recorder units. Results of our study with age-matched groups of healthy individuals (GrpH) and those with PD (GrpPD) showed the potential of SmartWalk to estimate the implication of task condition, pathways (with and without turn) and pathway segments (straight and turn) on one's knee flexion and gait with relevance to FoF. The knee flexion and gait-related indices were found to strongly corroborate with clinical measure related to FoF, particularly for GrpPD, serving as pre-clinical inputs for clinicians.

Comprehensive Understanding of Foot Development in Children Using Capacitive Textile Sensors

Knowledge of foot growth can provide information on the occurrence of children's growth spurts and an indication of the time to buy new shoes. Podiatrists still do not have enough evidence as to whether footwear influences the structural development of the feet and associated locomotor behaviours. Parents are only willing to buy an inexpensive brand, because children's shoes are deemed expendable due to their rapid foot growth. Consumers are not fully aware of footwear literacy; thus, views of consumers on children's shoes are left unchallenged. This study aims to embed knitted smart textile sensors in children's shoes to sense the growth and development of a child's feet-specifically foot length. Two prototype configurations were evaluated on 30 children, who each inserted their feet for ten seconds inside the instrumented shoes. Capacitance readings were related to the proximity of their toes to the sensor and validated against foot length and shoe size. A linear regression model of capacitance readings and foot length was developed. This regression model was found to be statistically significant (p-value = 0.01, standard error = 0.08). Results of this study indicate that knitted textile sensors can be implemented inside shoes to get a comprehensive understanding of foot development in children.

Tracking Day-To-Day Achilles Tendon Loading Progression During Rupture Recovery: A Case Study

Category: Sports; Basic Sciences/Biologics Introduction/Purpose: Achilles tendon rupture patients often suffer long-term functional deficits. Although progressive tendon loading improves healing, it is difficult to reliably measure in the real world and thus be precisely prescribed in rehabilitation. Modern wearable sensors, including instrumented shoe insoles, provide powerful platforms to measure real-world biomechanics. Using simple algorithms, we showed that these instrumented insoles can accurately quantify Achilles tendon loads. Yet, the feasibility of using wearables to enhance targeted Achilles tendon therapeutics remain unknown, partly due to the challenges of obtaining data on many patients over the long recovery process. Therefore, we leveraged a case study to verify whether instrumented insoles are able to track the longitudinal progression of Achilles tendon loading in daily life, and relate to clinically relevant events of tendon health. Methods: A patient (F, 30y/o) who underwent a right Achilles tendon repair was enrolled after consent in this IRB-approved study. During a standard rehabilitation protocol, an immobilizing boot fit with a 3-sensor instrumented insole (Loadsol) was worn starting from week 4 post-surgery. The insole remained in footwear after switching from boot to shoe, and data collection continued until week 22. The patient recorded &gt;10 seconds of insole data during gait each day, logged daily step count, and documented any event that may be related to tendon health, including pain and notable daily living activities. For each step identified by insole, we estimated Achilles tendon loads using our established algorithm, including load peak, impulse over a step, and load rates. We compared the daily average of these variables to self-reported events to explore their inter-relationships. We also correlated the load variables to determine whether they each provide unique insights into tendon loading. Results: The insole recorded up to 70 steps each day on a total of 116 days. Peak Achilles tendon load increased gradually yet non-linearly along the recovery process, with large variations between week 12-19 (Figure). 'Sharp' loading changes often corresponded to tendon health-related events, such as days of pain and swelling following rapid load increases in late week 12. A day of high step count (20k+) in week 18 was followed by a large decrease of the peak tendon load at the end of the same day. The insole also identified tendon load changes according to patient instructions, including a 65% increase in peak load by intentionally 'trying to push off' during gait. Finally, tendon load rates and impulse strongly correlated with peak load (R2 &gt;0.85). Conclusion: Longitudinally monitoring Achilles tendon loading is challenging because 1) it is limited by the scarce frequency of clinical visits, and 2) lab-based gait measurements do not faithfully reflect real-world biomechanics. Our first-of-kind case study shows the feasibility of using instrumented insoles to track day-to-day Achilles tendon loading in the real world. The results suggest Achilles tendon loading can be sufficiently tracked using peak load, and modified instantly and interactively via instructions or biofeedback. Our innovative paradigm empowers future studies to leverage accessible tools and deliver personalized rehabilitation according to quantitative guidance, thereby optimizing long-term Achilles tendon healing and functional recovery.

Validation of Instrumented Football Shoes to Measure On-Field Ground Reaction Forces.

Ground reaction forces (GRF) have been widely studied in football to prevent injury. However, ambulatory tools are missing, posing methodological limitations. The purpose of this study was to assess the validity of an innovative football shoe measuring normal GRF (nGRF) directly on the field through instrumented studs. A laboratory-based experiment was first conducted to compare nGRF obtained with the instrumented shoe (IS) to vertical GRF (vGRF) obtained with force platform (FP) data, the gold standard to measure vGRF. To this aim, three subjects performed 50 steps and 18 counter-movement jumps (CMJs). Secondly, eleven subjects completed running sprints at different velocities on a football field, as well as CMJs, while wearing the IS. Good to excellent agreement was found between the vGRF parameters measured with the FP and the nGRF measured by the IS (ICC > 0.75 for 9 out of 11 parameters). Moreover, on-field nGRF patterns demonstrated a progressive and significant increase in relation with the running velocity (p < 0.001). This study demonstrated that the IS is a highly valid tool to assess vGRF patterns on a football field. This innovative way to measure vGRF in situ could give new insights to quantify training load and detect neuromuscular fatigue.

Validity and Reliability of the Insole3 Instrumented Shoe Insole for Ground Reaction Force Measurement during Walking and Running.

Pressure-detecting insoles such as the Insole3 have potential as a portable alternative for assessing vertical ground reaction force (vGRF) outside of specialized laboratories. This study evaluated whether the Insole3 is a valid and reliable alternative to force plates for measuring vGRF. Eleven healthy participants walked overground at slow and moderately paced speeds and ran at a moderate pace while collecting vGRF simultaneously from a force plate (3000 Hz) and Insole3 (100 Hz). Intraclass correlation coefficients (ICC) demonstrated excellent vGRF agreement between systems during both walking speeds for Peak 1, Peak 2, the valley between peaks, and the vGRF impulse (ICC > 0.941). There was excellent agreement during running for the single vGRF peak (ICC = 0.942) and impulse (ICC = 0.940). The insoles slightly underestimated vGRF peaks (−3.7% to 0.9% bias) and valleys (−2.2% to −1.8% bias), and slightly overestimated impulses (4.2% to 5.6% bias). Reliability between visits for all three activities was excellent (ICC > 0.970). The Insole3 is a valid and reliable alternative to traditional force plates for assessing vGRF during walking and running in healthy adults. The excellent ICC values during slow walking suggests that the Insole3 may be particularly suitable for older adults in clinical and home settings.

Continuous Identification of Freezing of Gait in Parkinson’s Patients Using Artificial Neural Networks and Instrumented Shoes

Freezing of gait is an episodic phenomena faced by many patients with Parkinson's disease. It is characterized by episodes during which patients are unable to generate effective forward stepping movements, despite absence of motor deficits. During the onset of the event, the patients are less stable with statistically different stride width, toe in/out angle and center of pressure distance. It has been postulated that the degree of freezing can be reduced by providing external sensory feedback to the patients during the event. However, this intervention could be facilitated by accurate identification of freezing events in real-time. This manuscript presents an Artificial Neural Network model which uses signals recorded by an instrumented footwear to predict if a walking subject is having a freezing episode. Our model presented in this paper is capable of continuously predicting freezing of gait events at a high temporal resolution of 50 Hz, using a 0.5 second window of data recorded by the instrumented shoes, with a sensitivity of 96.0±2.5%, a specificity of 99.6±0.3%, a precision of 89.5±5.9%, and an accuracy of 99.5±0.4%. This algorithm was tested with data collected from 10 patients with Parkinson's disease with frequent freezing of gait episodes.

Use of the margin of stability to quantify stability in pathologic gait \u2013 a qualitative systematic review

BackgroundThe Margin of Stability (MoS) is a widely used objective measure of dynamic stability during gait. Increasingly, researchers are using the MoS to assess the stability of pathological populations to gauge their stability capabilities and coping strategies, or as an objective marker of outcome, response to treatment or disease progression. The objectives are; to describe the types of pathological gait that are assessed using the MoS, to examine the methods used to assess MoS and to examine the way the MoS data is presented and interpreted.MethodsA systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA) in the following databases: Web of Science, PubMed, UCL Library Explore, Cochrane Library, Scopus. All articles measured the MoS of a pathologically affected adult human population whilst walking in a straight line. Extracted data were collected per a prospectively defined list, which included: population type, method of data analysis and model building, walking tasks undertaken, and interpretation of the MoS.ResultsThirty-one studies were included in the final review. More than 15 different clinical populations were studied, most commonly post-stroke and unilateral transtibial amputee populations. Most participants were assessed in a gait laboratory using motion capture technology, whilst 2 studies used instrumented shoes. A variety of centre of mass, base of support and MoS definitions and calculations were described.ConclusionsThis is the first systematic review to assess use of the MoS and the first to consider its clinical application. Findings suggest the MoS has potential to be a helpful, objective measurement in a variety of clinically affected populations. Unfortunately, the methodology and interpretation varies, which hinders subsequent study comparisons. A lack of baseline results from large studies mean direct comparison between studies is difficult and strong conclusions are hard to make. Further work from the biomechanics community to develop reporting guidelines for MoS calculation methodology and a commitment to larger baseline studies for each pathology is welcomed.

269-OR: Thermal Regulation of the Diabetic Foot and Its Impact on Blood Perfusion

Diabetic foot ulcers (DFU) cause approximately 100,000 amputations every year in the US. Current preventive methods provide suboptimal prevention as several reports indicated that amputation rates are on the rise or have not decreased. Our group has previously developed temperature regulating insoles (TRI) that maintain plantar temperatures at 28°C, as previous research demonstrated that cooler tissue is resistant to ulceration. Our purpose in this study was to explore whether blood perfusion is affected by the cooling effect, via quantifying tissue oxygen saturation (StO2). Twelve subjects were recruited after providing informed consent. Inclusion criterion included being able to walk w/o assistance and not having active DFU. All subjects wore the instrumented shoes, with TRI only in the right shoe. Subjects completed two bouts of 5-minute walking on treadmill at self-selected speeds. Plantar temperatures and StO2 images were collected before and after treadmill walking with hyperspectral (Kent Imaging, CA) and thermal (FLIR® Systems, Inc, USA) cameras. Results indicated that while temperature regulation was on target in the forefoot and heel areas around 28°C (~4°C reduction compared to control side) the average difference in StO2 was only 3.0% (standard deviation of difference=2.8%, p=0.22). This suggests that cooling of the diabetic foot to prevent DFU does not necessarily lead to impaired blood perfusion. Disclosure A. Ersen: None. R. T. Myers: None. K. M. Raspovic: Consultant; Self; Orthofix Medical Inc. M. Ramos-roman: None. T. Lalli: None. Y. Salem: None. G. B. Hirschman: Board Member; Self; Vivonics Inc., Stock/Shareholder; Self; Vivonics Inc. M. Yavuz: None. Funding National Institutes of Health (R43DK109858, UL1TR001105)

Control and Evaluation of Body Weight Support Walker for Overground Gait Training

Gait rehabilitation training under robot-assisted partial Body Weight Support (BWS) is a promising technique that helps patients who suffer from a traumatic or congenital brain injury like stroke or cerebral palsy to become independent in daily life activities. In recent years, robotic BWS systems have been widely studied, where the BWS is provided by the robot while the user walks on devices fixed to the environment such as treadmills, thereby gaining functional benefits such as improved gait symmetry and increased walking speed. On the other hand, mobile BWS robots that allow conventional overground walking with well-designed control strategies have been less researched, limiting the widespread adoption of robotic rehabilitation because of the cost effectiveness of fixed robotic devices and poor portability. To address this problem, in our previous study, we developed a mobile BWS walker that allows for overground walking under variable levels of BWS. In this letter, we introduce a system architecture that integrates the walker with a pair of instrumented shoes and discuss different system control strategies including static and variable BWS control. When walking under Static-BWS (SBWS), the subject walks while a constant portion of his/her weight is supported, which might cause an unnatural gait. Using a Variable-BWS (VBWS), the provided BWS can be adjusted according to human's gait events to provide a more natural gait. This letter describes the system architecture, as well as experiments with able subjects that demonstrate the effectiveness of both the SBWS and VBWS control algorithms in relieving part of the subjects’ body weight. Specifically, by synchronizing the controlled BWS with human gait events, users were able to walk more naturally, particularly under a high level of BWS.

A shoe-mounted infrared sensor-based instrumentation for locomotion identification using machine learning methods

This paper deals with the identification of terrain that is crucial to trigger the damping in semi-active lower limb prosthesis. Objective: To identify level ground and ramp terrains using foot-to-ground angle (FGA) measurement. Methods: First, Instrumented shoe for FGA measurement was developed. Next, data collection from able-bodied (n = 5) and amputee (n = 1) participants was carried out. Finally, a comparison of identification accuracy using support vector machine (SVM) and convolution neural network (CNN) algorithms was done. Results: The average classification accuracy obtained for able-bodied participants and amputee is 79.57% ± 20.32% and 73.06% ± 12.70%, respectively using SVM, whereas it is 83.45% ± 14.50% and 80% ± 12.15% respectively using CNN. Our off-line analysis shows that overall, CNN outperformed SVM with an average of 4.86% increment in classification accuracy in able-bodied participants and 9.54% in an amputee. This study introduced a simplified, low-cost method for terrain identification in the prosthetic control application.

An Infrared Sensor-Based Instrumented Shoe for Gait Events Detection on Different Terrains and Transitions

This paper presents a low-cost wireless gait event detection system that incorporates infra-red range sensors mounted laterally at a specific anatomical location on the shoe. This system uses foot clearance information to extract heel strike (HS) and toe-off (TO) events. A subject-specific algorithm based on signature curve matching was developed to estimate the HS and TO in six able-bodied subjects and three transfemoral amputees. The data were acquired in a real-life environment while the subject walked on level ground and ramp terrains, including the transitions. The HS and TO in the level ground were detected with an accuracy of 22.87± 9.93 ms and 10.42± 6.70 ms, respectively, in able-bodied participants. The accuracy of 37.91± 12.36 ms and 20.41± 11.23 ms in HS and TO, respectively, was observed in amputees during level ground walking. Further, within the ramp terrain, the HS and TO were detected with an accuracy of 23.33± 11.20 ms and 13.36± 9.5 ms respectively in able-bodied subjects and 40.35± 12.64 ms and 47.51± 19.23 ms in amputees. This method reports comparable accuracy, with minimal standard deviation, to other existing methods based on accelerometer, gyroscope, electromyography, and force myography. This system is robust, easy to operate, and avoids direct contact with the body. The developed system offers a movable sensor platform in two degrees of freedom that facilitates the adaptability of the proposed system for different heel height and shoe sizes.

A Wearable Fall Detection System based on LoRa LPWAN Technology

The fall problem affects approximately one third of people aged over 65 years. Falls and fall-related injuries are one of the major causes of morbidity and mortality in the elderly population. Since many years, research activities have been targeted towards the development of technological solutions for the automatic detection and notification of falls. Among them, wearable based systems offer the advantage of being available ideally everywhere and cost-effective in terms of economy and computational burden. However, their use poses different challenges, from acceptability to battery usage. The choice of the communication technology, in particular, plays a fundamental role in the realization of a suitable solution, able to meet the target users’ needs. In this paper, we present a fall detection system, based on a pair of instrumented shoes. They communicate the alarming events to a supervising system through the LoRa LPWAN technology, without the need of a portable gateway. Experimental results demonstrate the effectiveness of the chosen communication technology and fall detection reliability.

Shoe-Integrated, Force Sensor Design for Continuous Body Weight Monitoring.

Traditional pedobarography methods use direct force sensor placement in the shoe insole to record pressure patterns. One problem with such methods is that they tap only a few points on the flat sole under the foot and, therefore, do not account for the total ground reaction force. As a result, body weight tends to be under-estimated. This disadvantage has made it more difficult for pedobarography to be used to monitor many diseases, especially when their symptoms include body weight changes. In this paper, the problem of pedobarographic body weight measurement is addressed using a novel ergonomic shoe-integrated sensor array architecture based on concentrating the applied force via three-layered structures that we call Sandwiched Sensor Force Consolidators (SSFC). A shoe prototype is designed with the proposed sensors and shown to accurately measure body weight with an achievable relative accuracy greater than 99%, even in the presence of motion. The achieved relative accuracy is at least 4X better than the existing state of the art. The SSFC shoe prototype is built using readily available soccer shoes and piezoresistive FlexiForce sensors. To improve the wearability and comfort of the instrumented shoe, a semi-computational sensor design methodology is developed based on an equivalent-area concept that can accurately account for SSFC’s with arbitrary shapes. The search space of the optimal SSFC design is shown to be combinatorial, and a high-performance computing (HPC) framework based on OpenMP parallel programming is proposed to accelerate the design optimization process. An optimal sensor design speedup of up to 22X is shown to be achievable using the HPC implementation.

Predicting vertical ground reaction force during running using novel piezoresponsive sensors and accelerometry

ABSTRACT Running is a common exercise with numerous health benefits. Vertical ground reaction force (vGRF) influences running injury risk and running performance. Measurement of vGRF during running is now primarily constrained to a laboratory setting. The purpose of this study was to evaluate a new approach to measuring vGRF during running. This approach can be used outside of the laboratory and involves running shoes instrumented with novel piezoresponsive sensors and a standard accelerometer. Thirty-one individuals ran at three different speeds on a force-instrumented treadmill while wearing the instrumented running shoes. vGRF was predicted using data collected from the instrumented shoes, and predicted vGRF were compared to vGRF measured via the treadmill. Per cent error of the resulting predictions varied depending upon the predicted vGRF characteristic. Per cent error was relatively low for predicted vGRF impulse (2–7%), active peak vGRF (3–7%), and ground contact time (3–6%), but relatively high for predicted vGRF load rates (22–29%). These errors should decrease with future iterations of the instrumented shoes and collection of additional data from a more diverse sample. The novel technology described herein might become a feasible way to collect large amounts of vGRF data outside of the traditional biomechanics laboratory.