Hybrid Soft-Rigid Active Prosthetics Laboratory Exercise for Hands-On Biomechanical and Biomedical Engineering Education.

This paper introduces a hands-on laboratory exercise focused on assembling and testing a hybrid soft-rigid active finger prosthetic for biomechanical and biomedical engineering (BME) education. This hands-on laboratory activity focuses on the design of a myoelectric finger prosthesis, integrating mechanical, electrical, sensor (i.e., inertial measurement units (IMUs), electromyography (EMG)), pneumatics, and embedded software concepts. We expose students to a hybrid soft-rigid robotic system, offering a flexible, modifiable lab activity that can be tailored to instructors' needs and curriculum requirements. All necessary files are made available in an open-access format for implementation. Off-the-shelf components are all purchasable through global vendors (e.g., DigiKey Electronics, McMaster-Carr, Amazon), costing approximately USD 100 per kit, largely with reusable elements. We piloted this lab with 40 undergraduate engineering students in a neural and rehabilitation engineering upper year elective course, receiving excellent positive feedback. Rooted in real-world applications, the lab is an engaging pedagogical platform, as students are eager to learn about systems with tangible impacts. Extensions to the lab, such as follow-up clinical (e.g., prosthetist) and/or technical (e.g., user-device interface design) discussion, are a natural means to deepen and promote interdisciplinary hands-on learning experiences. In conclusion, the lab session provides an engaging journey through the lifecycle of the prosthetic finger research and design process, spanning conceptualization and creation to the final assembly and testing phases.

Soft robotics-inspired sensing system for detecting downward movement and pistoning in prosthetic sockets: A proof-of-concept study.

BACKGROUND: Vertical displacement of the residual limb within transtibial prosthetic socket, often known as "pistoning" or downward movement, may lead to skin breakdowns and ulcers. Downward movement is particularly difficult to self-manage for diabetic individuals living with amputation because of diminished sensation in the residual limb from peripheral neuropathy. Therefore, a customizable sensor at the distal end that can alert the users when high-risk downward movement and pistoning occurs is urgently needed. OBJECTIVES: Presented herein for the first time is a lightweight, inexpensive sensing system inspired by soft robotics that can detect the occurrence and severity of downward movement at the distal end. METHODS: The sensing system consists of a multilayered torus-shaped balloon, allowing easy integration with pin-lock socket systems. The design allows sensing of vertical displacement without imparting high reaction forces back onto the distal end. A benchtop compression tester was used to characterize system performance. Systematic and parametric benchtop tests were conducted to examine the sensor's physical characteristics. Long-term (24-h) stability of the sensor was also recorded. RESULTS: Compared with water, air was determined to be a better medium with a higher linear full-scale span (FSS) because of its compressible nature. Repeatable 0.5-mm vertical displacements yielded a linear (>0.99 R2) FSS of 4.5 mm and a sensitivity of 0.8 kPa/mm. The sensing system is highly precise, with as low as 1% FSS total error band and average hysteresis of 2.84% of FSS. Over 24 h, a 4% FSS drift was observed. CONCLUSION: Sensing system characteristics, coupled with low-cost, customizable fabrication, indicates promising performance for daily use to notify and alert transtibial prosthetic users of downward movement and/or pistoning.

Temporal Eye-Hand Coordination During Visually Guided Reaching in 7- to 12-Year-Old Children With Strabismus.

Purpose: We recently found slow visually guided reaching in strabismic children, especially in the final approach. Here, we expand on those data by reporting saccade kinematics and temporal eye-hand coordination during visually guided reaching in children treated for strabismus compared with controls. Methods: Thirty children diagnosed with esotropia, a form of strabismus, 7 to 12 years of age and 32 age-similar control children were enrolled. Eye movements and index finger movements were recorded. While viewing binocularly, children reached out and touched a small dot that appeared randomly in one of four locations along the horizontal meridian (±5° or ±10°). Saccade kinematic measures (latency, accuracy and precision, peak velocity, and frequency of corrective and reach-related saccades) and temporal eye-hand coordination measures (saccade-to-reach planning interval, saccade-to-reach peak velocity interval) were compared. Factors associated with impaired performance were also evaluated. Results: During visually guided reaching, strabismic children had longer primary saccade latency (strabismic, 195 ± 29 ms vs. control; 175 ± 23 ms; P = 0.004), a 25% decrease in primary saccade precision (0.15 ± 0.06 vs. 0.12 ± 0.03; P = 0.007), a 45% decrease in the final saccade precision (0.16 ± 0.06 vs. 0.11 ± 0.03; P < 0.001), and more reach-related saccades (16 ± 13% of trials vs. 8 ± 6% of trials; P = 0.001) compared with a control group. No measurable stereoacuity was related to poor saccade kinematics. Conclusions: Strabismus impacts saccade kinematics during visually guided reaching in children, with poor binocularity playing a role in performance. Coupled with previous data showing slow reaching in the final approach, the current saccade data suggest that children treated for strabismus have not yet adapted or formed an efficient compensatory strategy during visually guided reaching.

Kinematics-Based Lower Limb Rehabilitation Monitoring Following Partial Knee Meniscectomy: Case Study.

Physiotherapy includes treatment to restore and optimize mobility after surgery, injury, disease, and/or degeneration. Based on assessments throughout the recovery process from visual observations of movement, exercises are prescribed to perform at home between clinic sessions. Although technical advances have facilitated remote communication between therapists and patients, accurate assessment of at-home exercises is challenged by a lack of direct observation. The current study advances remote assessment tools to assess key lower body exercises prescribed in a case study following recovery from arthroscopic partial meniscectomy (APM). Using Vicon motion capture, recovery metrics related to range of motion, strength, and gait function were extracted. Peak knee flexion angle on the operated leg during heel slide increased from 91.61° ± 4.17° to 127.42° ± 2.35° (p<0.05), although significant differences were found compared to the non-operated leg at Day 6 (138.19° ± 5.44°, p<0.05). Repetition times in heel slide and leg raise exercises on the affected leg decreased from Day 2 (2.74s) to Day 6 (1.07s), indicating strength recovery. Step length asymmetry decreased by 61.22% and step width asymmetry decreased by 41.75% from Day 2 to Day 6 post surgery, demonstrating improved gait function. This work presents a sample of automated recovery metrics that can be used for therapists to assess rehabilitation and inform the recovery process. Implications of the study findings on remote assessment using wearables are discussed. This work presents kinematics based quantifiable lower limb rehabilitation metrics to assess recovery objectives (e.g., knee flexion angle to assess knee range of motion) used by clinicians to inform recovery remotely.

Air microfluidics-enabled soft robotic transtibial prosthesis socket liner toward dynamic management of residual limb contact pressure and volume fluctuation.

Residual limb volume fluctuation and the resulting contact pressures are some of the key factors leading to skin ulcerations, suboptimal prosthetic functioning, pain, and diminishing quality of life of transtibial amputees. Self-management of socket fit is complicated by peripheral neuropathy, reducing the perception of pressure and pain in the residual limb. We introduce a novel proof-of-concept for a transtibial prosthetic socket liner with the potential to dynamically adjust the fit between the limb and socket. The core of the technology is a small air microfluidic chip (10 cm3 and 10 g) with 10 on-chip valves that enable sequential pressurizing of 10 actuators in custom sizes to match the pressures required by the residual limb's unique anatomy. The microfluidic chip largely reduced the number of electromechanical solenoid valves needed for sequential control of 10 actuators (2 instead of 10 valves), resulting in the reduction of the required power, size, mass, and cost of the control box toward an affordable and wearable prosthetic socket. Proof-of-concept testing demonstrated that the applied pressures can be varied in the desired sequence and to redistribute pressure. Future work will focus on integrating the system with biofidelic prosthetic sockets and residual limb models to investigate the ability to redistribute pressure away from pressure-sensitive regions (e.g., fibular head) to pressure tolerant areas. Overall, the dynamic prosthesis socket liner is very encouraging for creating a dynamic socket fit system that can be seamlessly integrated with existing socket fabrication methods for managing residual limb volume fluctuations and contact pressure.

Egocentric vision-based detection of surfaces: towards context-aware free-living digital biomarkers for gait and fall risk assessment.

BACKGROUND: Falls in older adults are a critical public health problem. As a means to assess fall risks, free-living digital biomarkers (FLDBs), including spatiotemporal gait measures, drawn from wearable inertial measurement unit (IMU) data have been investigated to identify those at high risk. Although gait-related FLDBs can be impacted by intrinsic (e.g., gait impairment) and/or environmental (e.g., walking surfaces) factors, their respective impacts have not been differentiated by the majority of free-living fall risk assessment methods. This may lead to the ambiguous interpretation of the subsequent FLDBs, and therefore, less precise intervention strategies to prevent falls. METHODS: With the aim of improving the interpretability of gait-related FLDBs and investigating the impact of environment on older adults' gait, a vision-based framework was proposed to automatically detect the most common level walking surfaces. Using a belt-mounted camera and IMUs worn by fallers and non-fallers (mean age 73.6 yrs), a unique dataset (i.e., Multimodal Ambulatory Gait and Fall Risk Assessment in the Wild (MAGFRA-W)) was acquired. The frames and image patches attributed to nine participants' gait were annotated: (a) outdoor terrains: pavement (asphalt, cement, outdoor bricks/tiles), gravel, grass/foliage, soil, snow/slush; and (b) indoor terrains: high-friction materials (e.g., carpet, laminated floor), wood, and tiles. A series of ConvNets were developed: EgoPlaceNet categorizes frames into indoor and outdoor; and EgoTerrainNet (with outdoor and indoor versions) detects the enclosed terrain type in patches. To improve the framework's generalizability, an independent training dataset with 9,424 samples was curated from different databases including GTOS and MINC-2500, and used for pretrained models' (e.g., MobileNetV2) fine-tuning. RESULTS: EgoPlaceNet detected outdoor and indoor scenes in MAGFRA-W with 97.36[Formula: see text] and 95.59[Formula: see text] (leave-one-subject-out) accuracies, respectively. EgoTerrainNet-Indoor and -Outdoor achieved high detection accuracies for pavement (87.63[Formula: see text]), foliage (91.24[Formula: see text]), gravel (95.12[Formula: see text]), and high-friction materials (95.02[Formula: see text]), which indicate the models' high generalizabiliy. CONCLUSIONS: Encouraging results suggest that the integration of wearable cameras and deep learning approaches can provide objective contextual information in an automated manner, towards context-aware FLDBs for gait and fall risk assessment in the wild.

Indoor Location Data for Tracking Human Behaviours: A Scoping Review.

Real-time location systems (RTLS) record locations of individuals over time and are valuable sources of spatiotemporal data that can be used to understand patterns of human behaviour. Location data are used in a wide breadth of applications, from locating individuals to contact tracing or monitoring health markers. To support the use of RTLS in many applications, the varied ways location data can describe patterns of human behaviour should be examined. The objective of this review is to investigate behaviours described using indoor location data, and particularly the types of features extracted from RTLS data to describe behaviours. Four major applications were identified: health status monitoring, consumer behaviours, developmental behaviour, and workplace safety/efficiency. RTLS data features used to analyse behaviours were categorized into four groups: dwell time, activity level, trajectory, and proximity. Passive sensors that provide non-uniform data streams and features with lower complexity were common. Few studies analysed social behaviours between more than one individual at once. Less than half the health status monitoring studies examined clinical validity against gold-standard measures. Overall, spatiotemporal data from RTLS technologies are useful to identify behaviour patterns, provided there is sufficient richness in location data, the behaviour of interest is well-characterized, and a detailed feature analysis is undertaken.

Reach Kinematics During Binocular Viewing in 7- to 12-Year-Old Children With Strabismus.

Purpose: Eye-hand coordination is essential for normal development and learning. Discordant binocular experience from childhood strabismus results in sensory and ocular motor impairments that can affect eye-hand coordination. We assessed reach kinematics during visually guided reaching in children treated for strabismus compared with controls. Methods: Thirty-six children aged 7 to 12 years diagnosed with esotropia, a form of strabismus, and a group of 35 age-similar control children were enrolled. Reach movements during visually guided reaching were recorded using the LEAP Motion Controller. While viewing binocularly, children reached out and touched a small dot that appeared randomly in one of four locations (±5° or ±10°). Kinematic measures were reach reaction time, total reach duration, peak velocity, acceleration duration, and deceleration duration. Touch accuracy and factors associated with impaired reach kinematics were evaluated. Results: Strabismic children had longer total reach duration (545 ± 60 ms vs. 504 ± 43 ms; P = 0.002), had longer deceleration duration (343 ± 54 ms vs. 312 ± 45 ms; P = 0.010), and were less accurate (93% ± 6% vs. 96% ± 5%, P = 0.007) than controls. No differences were found for reach reaction time, peak velocity, or acceleration duration (all Ps ≥ 0.197). Binocular dysfunction was more related to slow reaching than amblyopic eye visual acuity. Conclusions: Strabismus affects visually guided reaching in children, with slower reaching in the final approach and reduced endpoint accuracy. Binocular dysfunction was predictive of slow reaching. Unlike strabismic adults who show longer acceleration duration, longer deceleration in the final approach in strabismic children indicates a difference in control that could be due to reduced ability to use visual feedback.

Development of eye-hand coordination in typically developing children and adolescents assessed using a reach-to-grasp sequencing task.

Eye-hand coordination is required to accurately perform daily activities that involve reaching, grasping and manipulating objects. Studies using aiming, grasping or sequencing tasks have shown a stereotypical temporal coupling pattern where the eyes are directed to the object in advance of the hand movement, which may facilitate the planning and execution required for reaching. While the temporal coordination between the ocular and manual systems has been extensively investigated in adults, relatively little is known about the typical development of eye-hand coordination. Therefore, the current study addressed an important knowledge gap by characterizing the profile of eye-hand coupling in typically developing school-age children (n = 57) and in a cohort of adults (n = 30). Eye and hand movements were recorded concurrently during the performance of a bead threading task which consists of four distinct movements: reach to bead, grasp, reach to needle, and thread. Results showed a moderate to high correlation between eye and hand latencies in children and adults, supporting that both movements were planned in parallel. Eye and reach latencies, latency differences, and dwell time during grasping and threading, showed significant age-related differences, suggesting eye-hand coupling becomes more efficient in adolescence. Furthermore, visual acuity, stereoacuity and accommodative facility were also found to be associated with the efficiency of eye-hand coordination in children. Results from this study can serve as reference values when examining eye and hand movement during the performance of fine motor skills in children with neurodevelopmental disorders.

Fall risk assessment in the wild: A critical examination of wearable sensor use in free-living conditions.

BACKGROUND: Despite advances in laboratory-based supervised fall risk assessment methods (FRAs), falls still remain a major public health problem. This can be due to the alteration of behavior in laboratory due to the awareness of being observed (i.e., Hawthorne effect), the multifactorial complex etiology of falls, and our limited understanding of human behaviour in natural environments, or in the' wild'. To address these imitations, a growing body of literature has focused on free-living wearable-sensor-based FRAs. The objective of this narrative literature review is to discuss papers investigating natural data collected by wearable sensors for a duration of at least 24 h to identify fall-prone older adults. METHODS: Databases (Scopus, PubMed and Google Scholar) were searched for studies based on a rigorous search strategy. RESULTS: Twenty-four journal papers were selected, in which inertial sensors were the only wearable system employed for FRA in the wild. Gait was the most-investigated activity; but sitting, standing, lying, transitions and gait events, such as turns and missteps, were also explored. A multitude of free-living fall predictors (FLFPs), e.g., the quantity of daily steps, were extracted from activity bouts and events. FLFPs were further categorized into discrete domains (e.g., pace, complexity) defined by conceptual or data-driven models. Heterogeneity was found within the reviewed studies, which includes variance in: terminology (e.g., quantity vs macro), hyperparameters to define/estimate FLFPs, models and domains, and data processing approaches (e.g., the cut-off thresholds to define an ambulatory bout). These inconsistencies led to different results for similar FLFPs, limiting the ability to interpret and compare the evidence. CONCLUSION: Free-living FRA is a promising avenue for fall prevention. Achieving a harmonized model is necessary to systematically address the inconsistencies in the field and identify FLFPs with the highest predictive values for falls to eventually address intervention programs and fall prevention.

Test-retest repeatability reveals a temporal kinematic signature for an upper limb precision grasping task in adults.

Hand-eye coordination skills, such as reaching and grasping, are fundamentally important for the performance of most daily activities. Upper limb kinematics recorded by motion tracking systems provide detailed insight into the central nervous system control of movement planning and execution. For example, kinematic metrics can reveal deficits in control, and compensatory neuromotor strategies in individuals with neuropathologies. However, the clinical utility of kinematic metrics is currently limited because their psychometric properties, such as test-retest repeatability, have not been well characterized. Therefore, the purpose of this study was to examine the degree of repeatability of spatiotemporal kinematic metrics and determine which, if any, measures form a kinematic signature for a precision grasping task. Healthy adults (n = 40) were tested on two occasions separated by 5-10 days on a bead threading task consisting of reaching and precision grasping. Results showed good test-retest repeatability for reach peak velocity, reach and grasp durations, whereas poor to moderate reliability was observed for measures of spatial precision and maximum grip aperture. In addition, analysis showed that reliable estimates of kinematic metrics can be obtained using 10 trials. Overall, our results indicate that reach peak velocity and temporal metrics form a stable characteristic, or a kinematic signature, of individual performance on a standardized bead threading task. These findings suggest potential utility in applying kinematic metrics for clinical assessment of upper limb reaching tasks.

Learning-Aided User Intent Estimation for Smart Rollators.

With the aging population and rising rates of mobility disability, the demand for advanced smart rollators is increasing. To design control systems which improve safety and reliability, accurate prediction of human intent is required. In this paper, we present a classification method to predict intent of the rollator user using indirect inputs. The proposed classification algorithm uses data collected from an inertial measurement unit and an encoder implemented into a rollator. The developed intent estimation method is experimentally verified on our modified robotic platform. For our experiment with 7 healthy young adults, KNN classification algorithm was able to predict 3 intents (turn left, turn right and walk straight) with 92.9 % accuracy.

Early Aggressive Immunotherapy Improves Functional Outcome in Chronic Immune Sensory Polyradiculopathy.

Chronic immune sensory polyradiculopathy (CISP) is an uncommon and treatable inflammatory disorder of the proximal sensory nerve roots. Patients typically present with severe sensory ataxia, normal motor examination, unsteady gait, and normal nerve conduction studies (NCS). We describe an elderly man who presented with a two-week history of progressive numbness of both legs and recurrent falls. He had hyporeflexia, normal strength, severe proprioceptive, and vibration sense loss in both lower limbs and was unable to stand or walk because of severe sensory ataxia. The NCS and MR scan of the spine were normal. Tibial somatosensory evoked potentials revealed proximal conduction defect and localized the pathology to the lumbar sensory nerve roots proximal to the dorsal root ganglion. Cerebrospinal fluid showed cytoalbuminergic dissociation suggestive of inflammation. CISP was diagnosed; he was given aggressive immunotherapy consisting sequentially of corticosteroids with mycophenolate mofetil and three cycles of intravenous immunoglobulin after which he regained independent mobility. Unlike previous reports where patients presented months-years after symptom onset and improved after single-line immunotherapy, our patient presented fairly acutely and made dramatic improvement only after aggressive combination therapy. We urge physicians to recognize this uncommon neurologic cause of sensory ataxia where early aggressive treatment is crucial for better functional outcomes.

Concurrent maturation of visuomotor skills and motion perception in typically-developing children and adolescents.

Perceptual and visuomotor skills undergo considerable development from early childhood into adolescence; however, the concurrent maturation of these skills has not yet been examined. This study assessed visuomotor function and motion perception in a cross-section of 226 typically-developing children between 4 and 16 years of age. Participants were tested on three tasks hypothesized to engage the dorsal visual stream: threading a bead on a needle, marking dots using a pen, and discriminating form defined by motion contrast. Mature performance was reached between 8 and 12 years, with youngest maturation for kinematic measures for a reach-to-grasp task, and oldest maturation for a precision tapping task. Performance on the motion perception task shared no association with motor skills after controlling for age.

Automated Detection of Multidirectional Compensatory Balance Reactions: A Step Towards Tracking Naturally Occurring Near Falls.

Falls are the leading cause of fatal and non-fatal injuries among seniors with serious and costly consequences. Laboratory evidence supports the view that impaired ability to execute compensatory balance reactions (CBRs) or near-falls is linked to an increased risk of falling. Therefore, as an alternative to the commonly used fall risk assessment methods examining spatial-temporal parameters of gait, this study focuses on the development of machine learning-based models to detect multidirectional CBRs using wearable inertial measurement units (IMUs). Random forest models were developed based upon the data captured by five wearable IMUs to 1) detect CBRs during normal gait, and 2) identify the type of CBR (eight different classes). A perturbation treadmill (PT) was employed to systematically elicit CBRs (i.e. PT-CBRs) during walking in different directions (e.g slip-like, trip-like, and medio-lateral) and amplitudes (e.g., low-, high-amplitude). We hypothesized that these PT-CBRs could simulate naturally-occurring CBRs (N-CBRs). Proof-of-concept testing in 9 young, healthy adults demonstrated accuracies of 96.60% and 80.64% for the PT-CBR detection and type identification models, respectively. Performance of the detection model was tested against a published dataset (IMUFD) simulating N-CBRs, including the most common types observed in older adults in long-term care facilities, which achieved sensitivity of 100%, but poor specificity. Adding normal gait data from IMUFD for training improved specificity, indicating treadmill walking alone is insufficient exemplar data. Perturbation treadmill combined with overground walking data is a suitable paradigm to collect training datasets of involuntary CBR events. These findings suggest that accurate detection of naturally-occurring CBRs is feasible, and supports further investigation of implementing a wearable sensor system to track naturally-occurring CBRs as a novel means of fall risk assessment.

Effect of Visual Information on Dominant and Non-dominant Hands During Bimanual Drawing with a Robotic Platform.

In a stable bimanual trajectory tracing task with interlimb spatial and temporal synchrony, blocking the visual information from one hand may alter the performance of either hand. In this paper, we investigate the effect of visual information on motor behaviour of dominant and non-dominant hands during a bimanual task, with a focus on motor lateralization theory's anticipation for a more pronounced distortion on one hand due to visual information withdrawal. To address this question, four bimanual circle tracing experiments were designed with two rehabilitation robotic arms with real time visual feedback. Two experiments were conducted under the free-visual condition whereas the visual feedback from one hand was blocked for the other two. The in-depth analysis of the metrics extracted from 685 circles, drawn by 6 participants, revealed that non-dominant hand, when visible, generally performs worse than the dominant hand, for instance it exhibits less circularity. In their invisible modes, the performance of the dominant and non-dominant hands displayed inconsistent difference across the participants. Moreover, both hands showed a higher pace when partial visual information was available. Our findings using this robotic framework as a systematic tool on developing new paradigms are discussed.

IMU, sEMG, or their cross-correlation and temporal similarities: Which signal features detect lateral compensatory balance reactions more accurately?

BACKGROUND AND OBJECTIVE: Falls are the leading cause of fatal and non-fatal injuries among seniors worldwide. While laboratory evidence supports the view that impaired ability to execute compensatory balance responses (CBRs) is linked to an increased risk of falling, existing unsupervised fall risk assessment methods are mainly focused on detecting changes in spatio-temporal gait parameters over time rather than naturally-occurring CBR events. To address the gap in available methods, this paper compares the capability of machine learning-based models trained on the kinematic data from inertial measurement units (IMU) and surface electromyography (sEMG) features to detect lateral CBRs, to ultimately address detection of CBRs in free-living conditions. Moreover, we propose a novel "Hybrid" feature set, which considers cross-correlation and temporal similarities between the normalized kinematic and sEMG signals. METHODS: Focusing on frontal plane perturbations, a classifier to automatically: 1) detect lateral CBRs during normal gait, and 2) identify type (i.e., crossover, sidestep) using data from three wearable IMUs and 4 sEMG signals from the thigh (i.e., biceps femoris, rectus femoris) and lower leg muscles (i.e., gastrocnemious, tibialis anterior) was developed. In total, 600 trials (including 358 lateral CBRs) from 7 young, healthy adults were analyzed. The effects of feature type (IMU, sEMG, Hybrid) and sensor placement on the random forest-based classifier performance were investigated. RESULTS: CBR detection (i.e., CBR vs normal gait) accuracies (leave-one-subject-out cross validation) were 83.95% and 99.21% using sEMG-based and IMU-based features, respectively, which dropped to 72.17% and 84.83% for the multiclass identification (i.e., side-step vs cross-over vs normal gait) problem. Findings yielded shank as the best overall location for the multiclass problem, and chest as the most accurate for CBR detection. In general, adding sEMG and Hybrid features to IMUs yielded incremental improvements in CBR detection and type identification (87.03% leave-one-subject-out cross-validation for type identification). CONCLUSION: The findings of this study demonstrate that IMU-based features are favourable over sEMG and Hybrid features for the task of CBR detection, with incremental value for type identification. Evidence presented suggests that Hybrid features may increase performance for other wearable sensor applications (e.g. activity recognition systems).

Evaluation of the Leap Motion Controller during the performance of visually-guided upper limb movements.

Kinematic analysis of upper limb reaching provides insight into the central nervous system control of movements. Until recently, kinematic examination of motor control has been limited to studies conducted in traditional research laboratories because motion capture equipment used for data collection is not easily portable and expensive. A recently developed markerless system, the Leap Motion Controller (LMC), is a portable and inexpensive tracking device that allows recording of 3D hand and finger position. The main goal of this study was to assess the concurrent reliability and validity of the LMC as compared to the Optotrak, a criterion-standard motion capture system, for measures of temporal accuracy and peak velocity during the performance of upper limb, visually-guided movements. In experiment 1, 14 participants executed aiming movements to visual targets presented on a computer monitor. Bland-Altman analysis was conducted to assess the validity and limits of agreement for measures of temporal accuracy (movement time, duration of deceleration interval), peak velocity, and spatial accuracy (endpoint accuracy). In addition, a one-sample t-test was used to test the hypothesis that the error difference between measures obtained from Optotrak and LMC is zero. In experiment 2, 15 participants performed a Fitts' type aiming task in order to assess whether the LMC is capable of assessing a well-known speed-accuracy trade-off relationship. Experiment 3 assessed the temporal coordination pattern during the performance of a sequence consisting of a reaching, grasping, and placement task in 15 participants. Results from the t-test showed that the error difference in temporal measures was significantly different from zero. Based on the results from the 3 experiments, the average temporal error in movement time was 40±44 ms, and the error in peak velocity was 0.024±0.103 m/s. The limits of agreement between the LMC and Optotrak for spatial accuracy measures ranged between 2-5 cm. Although the LMC system is a low-cost, highly portable system, which could facilitate collection of kinematic data outside of the traditional laboratory settings, the temporal and spatial errors may limit the use of the device in some settings.

User Acceptance of Wrist-Worn Activity Trackers Among Community-Dwelling Older Adults: Mixed Method Study.

BACKGROUND: Wearable activity trackers are newly emerging technologies with the anticipation for successfully supporting aging-in-place. Consumer-grade wearable activity trackers are increasingly ubiquitous in the market, but the attitudes toward, as well as acceptance and voluntary use of, these trackers in older population are poorly understood. OBJECTIVE: The aim of this study was to assess acceptance and usage of wearable activity trackers in Canadian community-dwelling older adults, using the potentially influential factors as identified in literature and technology acceptance model. METHODS: A mixed methods design was used. A total of 20 older adults aged 55 years and older were recruited from Southwestern Ontario. Participants used 2 different wearable activity trackers (Xiaomi Mi Band and Microsoft Band) separately for each segment in the crossover design study for 21 days (ie, 42 days total). A questionnaire was developed to capture acceptance and experience at the end of each segment, representing 2 different devices. Semistructured interviews were conducted with 4 participants, and a content analysis was performed. RESULTS: Participants ranged in age from 55 years to 84 years (mean age: 64 years). The Mi Band gained higher levels of acceptance (16/20, 80%) compared with the Microsoft Band (10/20, 50%). The equipment characteristics dimension scored significantly higher for the Mi Band (P<.05). The amount a participant was willing to pay for the device was highly associated with technology acceptance (P<.05). Multivariate logistic regression with 3 covariates resulted in an area under the curve of 0.79. Content analysis resulted in the formation of the following main themes: (1) smartphones as facilitators of wearable activity trackers; (2) privacy is less of a concern for wearable activity trackers, (3) value proposition: self-awareness and motivation; (4) subjective norm, social support, and sense of independence; and (5) equipment characteristics matter: display, battery, comfort, and aesthetics. CONCLUSIONS: Older adults were mostly accepting of wearable activity trackers, and they had a clear understanding of its value for their lives. Wearable activity trackers were uniquely considered more personal than other types of technologies, thereby the equipment characteristics including comfort, aesthetics, and price had a significant impact on the acceptance. Results indicated that privacy was less of concern for older adults, but it may have stemmed from a lack of understanding of the privacy risks and implications. These findings add to emerging research that investigates acceptance and factors that may influence acceptance of wearable activity trackers among older adults.

Measurement of peak impact loads differ between accelerometers - Effects of system operating range and sampling rate.

A wide variety of accelerometer systems, with differing sensor characteristics, are used to detect impact loading during physical activities. The study examined the effects of system characteristics on measured peak impact loading during a variety of activities by comparing outputs from three separate accelerometer systems, and by assessing the influence of simulated reductions in operating range and sampling rate. Twelve healthy young adults performed seven tasks (vertical jump, box drop, heel drop, and bilateral single leg and lateral jumps) while simultaneously wearing three tri-axial accelerometers including a criterion standard laboratory-grade unit (Endevco 7267A) and two systems primarily used for activity-monitoring (ActiGraph GT3X+, GCDC X6-2mini). Peak acceleration (gmax) was compared across accelerometers, and errors resulting from down-sampling (from 640 to 100Hz) and range-limiting (to ±6g) the criterion standard output were characterized. The Actigraph activity-monitoring accelerometer underestimated gmax by an average of 30.2%; underestimation by the X6-2mini was not significant. Underestimation error was greater for tasks with greater impact magnitudes. gmax was underestimated when the criterion standard signal was down-sampled (by an average of 11%), range limited (by 11%), and by combined down-sampling and range-limiting (by 18%). These effects explained 89% of the variance in gmax error for the Actigraph system. This study illustrates that both the type and intensity of activity should be considered when selecting an accelerometer for characterizing impact events. In addition, caution may be warranted when comparing impact magnitudes from studies that use different accelerometers, and when comparing accelerometer outputs to osteogenic impact thresholds proposed in literature.