Investigating the clinical utility of wearable motion sensors to guide therapy in children with cerebral palsy

Background: Children with cerebral palsy (CP) experience a wide range of motor impairments and rarely achieve the recommended level of daily physical activity. To recognise environmental barriers and facilitators, clinicians depend upon an objective evaluation of performance in daily life. Wearable inertial sensors (Physilog®) have recently been developed to measure meaningful spatio-temporal gait parameters. In this study, we investigated the clinical utility of wearable sensors to guide therapy in children with CP. Methods: 9 patients with CP wore inertial sensors at baseline (= week 0), at pre- (= week 4) and post-intervention (= week 8) and follow-up (= week 12). Physiotherapists were asked to develop the intervention phase (i.e., a training plan integrated in their patient’s daily routine) according to the sensors outcomes. To assess the clinical utility of inertial sensors, we designed three different questionnaires for the patients, caregivers and physiotherapists, respectively. The answers were recorded using a visual analogue scale (VAS; 0 representing the worst score, 100 representing the best score; ≤30 not satisfied, 31–69 average, ≥70 satisfied) and comments were noted down during the interviews. Furthermore, technical problems and training plans were gathered in a case report form. Results: Overall, patients were satisfied with the sensors (mean 70.6 - 87.4) but experienced tiredness (mean 53.4) during the month of personal training. Caregivers found the sensors useful (mean 77.4) and six out of eight parents noticed an improvement of their child’s physical performance. All physiotherapists would consider using sensors in their practice (mean 82.0) even though they scored their usefulness as average (mean 66.0). Despite having a better representation of patients’ physical activities with sensors (mean 70.0), physiotherapists had trouble adapting the exercises proposed to their patients (mean 49.0). Conclusion: Despite some technical issues, Physilog® sensors presented fairly good acceptability and practicability. Nevertheless, several physiotherapists faced difficulties in adapting existing therapy according to sensor outcomes. Therefore, the implementation of the sensors in clinics to guide therapy will require further adaptations of the setting to increase its relevance

Body sensor networks: smart monitoring solutions after reconstructive surgery

Advances in reconstructive surgery are providing treatment options in the face of major trauma and cancer. Body Sensor Networks (BSN) have the potential to offer smart solutions to a range of clinical challenges. The aim of this thesis was to review the current state of the art devices, then develop and apply bespoke technologies developed by the Hamlyn Centre BSN engineering team supported by the EPSRC ESPRIT programme to deliver post-operative monitoring options for patients undergoing reconstructive surgery. A wireless optical sensor was developed to provide a continuous monitoring solution for free tissue transplants (free flaps). By recording backscattered light from 2 different source wavelengths, we were able to estimate the oxygenation of the superficial microvasculature. In a custom-made upper limb pressure cuff model, forearm deoxygenation measured by our sensor and gold standard equipment showed strong correlations, with incremental reductions in response to increased cuff inflation durations. Such a device might allow early detection of flap failure, optimising the likelihood of flap salvage. An ear-worn activity recognition sensor was utilised to provide a platform capable of facilitating objective assessment of functional mobility. This work evolved from an initial feasibility study in a knee replacement cohort, to a larger clinical trial designed to establish a novel mobility score in patients recovering from open tibial fractures (OTF). The Hamlyn Mobility Score (HMS) assesses mobility over 3 activities of daily living: walking, stair climbing, and standing from a chair. Sensor-derived parameters including variation in both temporal and force aspects of gait were validated to measure differences in performance in line with fracture severity, which also matched questionnaire-based assessments. Monitoring the OTF cohort over 12 months with the HMS allowed functional recovery to be profiled in great detail. Further, a novel finding of continued improvements in walking quality after a plateau in walking quantity was demonstrated objectively. The methods described in this thesis provide an opportunity to revamp the recovery paradigm through continuous, objective patient monitoring along with self-directed, personalised rehabilitation strategies, which has the potential to improve both the quality and cost-effectiveness of reconstructive surgery services.Open Acces

Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice

This Special Issue shows a range of potential opportunities for the application of wearable movement sensors in motor rehabilitation. However, the papers surely do not cover the whole field of physical behavior monitoring in motor rehabilitation. Most studies in this Special Issue focused on the technical validation of wearable sensors and the development of algorithms. Clinical validation studies, studies applying wearable sensors for the monitoring of physical behavior in daily life conditions, and papers about the implementation of wearable sensors in motor rehabilitation are under-represented in this Special Issue. Studies investigating the usability and feasibility of wearable movement sensors in clinical populations were lacking. We encourage researchers to investigate the usability, acceptance, feasibility, reliability, and clinical validity of wearable sensors in clinical populations to facilitate the application of wearable movement sensors in motor rehabilitation

Machine Learning-based Detection of Compensatory Balance Responses and Environmental Fall Risks Using Wearable Sensors

Falls are the leading cause of fatal and non-fatal injuries among seniors worldwide, with serious and costly consequences. Compensatory balance responses (CBRs) are reactions to recover stability following a loss of balance, potentially resulting in a fall if sufficient recovery mechanisms are not activated. While performance of CBRs are demonstrated risk factors for falls in seniors, the frequency, type, and underlying cause of these incidents occurring in everyday life have not been well investigated. This study was spawned from the lack of research on development of fall risk assessment methods that can be used for continuous and long-term mobility monitoring of the geri- atric population, during activities of daily living, and in their dwellings. Wearable sensor systems (WSS) offer a promising approach for continuous real-time detection of gait and balance behavior to assess the risk of falling during activities of daily living. To detect CBRs, we record movement signals (e.g. acceleration) and activity patterns of four muscles involving in maintaining balance using wearable inertial measurement units (IMUs) and surface electromyography (sEMG) sensors. To develop more robust detection methods, we investigate machine learning approaches (e.g., support vector machines, neural networks) and successfully detect lateral CBRs, during normal gait with accuracies of 92.4% and 98.1% using sEMG and IMU signals, respectively. Moreover, to detect environmental fall-related hazards that are associated with CBRs, and affect balance control behavior of seniors, we employ an egocentric mobile vision system mounted on participants chest. Two algorithms (e.g. Gabor Barcodes and Convolutional Neural Networks) are developed. Our vision-based method detects 17 different classes of environmental risk factors (e.g., stairs, ramps, curbs) with 88.5% accuracy. To the best of the authors knowledge, this study is the first to develop and evaluate an automated vision-based method for fall hazard detection

Wearable Technologies to Support Lower Limb Rehabilitation and Clinical Practice: user requirements, design and evaluation

The widespread adoption of wearable technologies in healthcare has the potential to bring about significant improvements. However, these technologies face design challenges when applied in real world settings and must be tailored to specific contexts of use and the needs of a diverse user base. This thesis investigates these issues in two distinct yet related areas of healthcare: neurorehabilitation and clinical movement analysis. In neurorehabilitation, the research builds on previous work that demonstrated the effectiveness of wearable rhythmic haptic metronomes in improving and measuring the gait of individuals with neurological conditions in laboratory settings. This study takes this approach into the community and care home settings, using a technology probe method to identify the real-life requirements and design considerations of potential end-users and clinicians. This process identified a range of physical, sensory, and cognitive issues that are relevant to the design of the haptic metronomes, including haptic perception ability, wearability, interaction techniques, and individual preferences for body placement. The second part of the thesis initially focused on the potential of active cueing for musculoskeletal conditions, but formative discussions with specialist physiotherapists and orthopaedic surgeons suggested that wearable clinical movement analysis would be a more suitable focus. Currently, proprietary systems for objectively assessing lower limb movements are either poorly suited or too expensive. To address this gap, non-proprietary software called MoJoXlab, paired with low-cost wearable inertial sensors was validated against high-end commercial software to perform clinical movement analysis. The results of these tests were compared across a range of activities, including walking, squatting, and jumping. MoJoXlab was further validated with a different sensor system, and limitations and nuances of supporting multiple sensor systems were identified. Overall, this thesis highlights the importance of considering the needs and preferences of diverse users and the specific conditions and contexts in which wearable technologies will be used to effectively design and implement these technologies in healthcare

Rehabilitation:mobility, exercise & sports; a critical position stand on current and future research perspectives

Background Human movement, rehabilitation, and allied sciences have embraced their ambitions within the cycle of “RehabMove” congresses over the past 30 years. This combination of disciplines and collaborations in the Netherlands has tried to provide answers to questions in the fields of rehabilitation and adapted sports, while simultaneously generating new questions and challenges. These research questions help us to further deepen our understanding of (impaired) human movement and functioning, with and without supportive technologies, and stress the importance of continued multidisciplinary (inter)national collaboration. Methods This position stand provides answers that were conceived by the authors in a creative process underlining the preparation of the 6th RehabMove Congress. Results The take-home message of the RehabMove2018 Congress is a plea for continued multidisciplinary research in the fields of rehabilitation and adapted sports. This should be aimed at more individualized notions of human functioning, practice, and training, but also of performance, improved supportive technology, and appropriate “human and technology asset management” at both individual and organization levels and over the lifespan. Conclusions With this, we anticipate to support the development of rehabilitation sciences and technology and to stimulate the use of rehabilitation notions in general health care. We also hope to help ensure a stronger embodiment of preventive and lifestyle medicine in rehabilitation practice. Indeed, general health care and rehabilitation practice require a healthy and active lifestyle management and research agenda in the context of primary, secondary, and tertiary prevention. IMPLICATIONS FOR REHABILITATION Continued multidisciplinary (international) collaboration will stimulate the development of rehabilitation and human movement sciences. Notions from “human and technology asset management and ergonomics” are fundamental to rehabilitation practice and research. The rehabilitation concept will further merge into general health care and the quality there-off

Exploring Wearable Technologies for Health Monitoring: Applications in Motion Sickness and Dehydration

Wearable devices have enhanced health monitoring in clinical settings by effectively measuring physiological signals to inform prevention strategies. With the rapid development of sensors and data-driven decision-making, wearables can be applied in non-clinical settings to monitor various health conditions. Oftentimes, the most direct, accurate measurements are inaccessible or impractical during real-life, unscripted daily activities (e.g., equipment access). In this dissertation, signal-based models were developed to evaluate common wearables for health monitoring, with specific applications on motion sickness and dehydration. Motion sickness can range from stomach discomfort to severe nausea and affects passengers more frequently than drivers. As automated vehicles and mobility solutions become normalized, motion sickness incidence is anticipated to increase among on-road passengers. As such, there is a greater need for early detection of vehicular motion sickness. Previous studies have shown postural instability to be associated with motion sickness. Therefore, assessments of standing balance may be useful for estimating levels of motion sickness. However, there are limited studies of post-drive standing balance that have been conducted in passenger vehicles or under ecologically-relevant conditions. In this dissertation, three studies quantified motion sickness and standing balance of vehicle passengers following continuous driving exposures deployed on a closed test track and on-road environments using a wearable inertial measurement unit. In the closed test track study, trunk postural sway increased significantly during the more challenging balance exercises. Post-drive changes to postural sway metrics (e.g., sway velocity and path length) were larger for drives during which participants performed a visual-based task on a handheld tablet-based device, as compared to drives without a task. In the on-road study, changes in post-drive postural sway were consistent with the findings from the closed test track study. However, there was no meaningful effect of performing a task on changes in postural sway metrics. In the third study, significant changes in post-drive postural sway were associated with the severest motion sickness responses, suggesting that sway metrics could characterize motion sickness. While preliminary, these findings could inform monitoring approaches of vehicular motion sickness using postural sway data from wearable sensors. Additional work would further explore wearables as a potential screening tool for motion sickness susceptibility prior to the drive. In the fourth study of this dissertation, wearables were used to develop a noninvasive method for continuously measuring dehydration; untreated, dehydration can lead to performance detriments and in severe cases, death due to heat-related complications. Participants performed a series of orthostatic postural movements before and after a cycling session while donning common wearable that measured heart rate and trunk kinematic data. A machine learning model was trained and accurately classified a level of fluid loss equivalent to 2% of bodyweight. Using data from wearable devices, this method can support preemptive fluid replenishment and subsequently minimize potential decreases in performance; reduce the risk of serious heat injuries; and inform users to take additional hydration assessments. These findings demonstrated the feasibility of wearable technologies for monitoring health conditions that are difficult to assess in non-clinical settings. Specifically, this dissertation developed models that could relate motion sickness and post-drive postural sway measured from wearable devices, and could reliably leverage common sensor-based signals to minimize dehydration. Future applications with wearable devices could especially support secondary prevention strategies, which are approaches aimed at minimizing the impacts of health conditions once they have occurred.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169663/1/victle_1.pd

Human Health Engineering Volume II

In this Special Issue on “Human Health Engineering Volume II”, we invited submissions exploring recent contributions to the field of human health engineering, i.e., technology for monitoring the physical or mental health status of individuals in a variety of applications. Contributions could focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing physiological variables, papers highlighting health-monitoring applications, and examples of control and process management applications for human health. In comparison to biomedical engineering, we envision that the field of human health engineering will also cover applications for healthy humans (e.g., sports, sleep, and stress), and thus not only contribute to the development of technology for curing patients or supporting chronically ill people, but also to more general disease prevention and optimization of human well-being

Proceedings XXIII Congresso SIAMOC 2023

Il congresso annuale della Società Italiana di Analisi del Movimento in Clinica (SIAMOC), giunto quest’anno alla sua ventitreesima edizione, approda nuovamente a Roma. Il congresso SIAMOC, come ogni anno, è l’occasione per tutti i professionisti che operano nell’ambito dell’analisi del movimento di incontrarsi, presentare i risultati delle proprie ricerche e rimanere aggiornati sulle più recenti innovazioni riguardanti le procedure e le tecnologie per l’analisi del movimento nella pratica clinica. Il congresso SIAMOC 2023 di Roma si propone l’obiettivo di fornire ulteriore impulso ad una già eccellente attività di ricerca italiana nel settore dell’analisi del movimento e di conferirle ulteriore respiro ed impatto internazionale. Oltre ai qualificanti temi tradizionali che riguardano la ricerca di base e applicata in ambito clinico e sportivo, il congresso SIAMOC 2023 intende approfondire ulteriori tematiche di particolare interesse scientifico e di impatto sulla società. Tra questi temi anche quello dell’inserimento lavorativo di persone affette da disabilità anche grazie alla diffusione esponenziale in ambito clinico-occupazionale delle tecnologie robotiche collaborative e quello della protesica innovativa a supporto delle persone con amputazione. Verrà infine affrontato il tema dei nuovi algoritmi di intelligenza artificiale per l’ottimizzazione della classificazione in tempo reale dei pattern motori nei vari campi di applicazione

Topics in construction safety and health : falls : an interdisciplinary annotated bibliography

"These referenced articles provide literature on falls by construction workers and their risks on the job." - NIOSHTIC-2NIOSHTIC no. 20068247Production of this document was supported by cooperative agreement OH 009762 from the National Institute for Occupational Safety and Health (NIOSH). The contents are solely the responsibility of the authors and do not necessarily represent the official views of NIOSH.Falls-annotated-bibliography.pdfcooperative agreement OH 009762 from the National Institute for Occupational Safety and Healt