Wearable sensors: At the frontier of personalised health monitoring, smart prosthetics and assistive technologies

Khoshmanesh, Farnaz; Thurgood, Peter; Pirogova, Elena; Nahavandi, Saeid; Baratchi, Sara

doi:10.1016/j.bios.2020.112946

Cited by 128 publications

(88 citation statements)

References 178 publications

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“…In general, the included studies' findings described how physiological monitoring could report diverse occupational health risks and how these variables respond differently based on individual differences. Monitoring physiological responses in real-time would allow for the possibility of adaptations to optimise an individual's performance in the face of the developed task and according to his capabilities [98]. Combined with contextual data, physiological variables provide valuable tools for enhancing assessment procedures adapted to tasks' characteristics.…”

Section: Other Monitored Variablesmentioning

confidence: 99%

Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review

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Baptista

et al. 2021

Sensors

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The emergence of physiological monitoring technologies has produced exceptional opportunities for real-time collection and analysis of workers’ physiological information. To benefit from these safety and health prognostic opportunities, research efforts have explored the applicability of these devices to control workers’ wellbeing levels during occupational activities. A systematic review is proposed to summarise up-to-date progress in applying physiological monitoring systems for occupational groups. Adhering with the PRISMA Statement, five databases were searched from 2014 to 2021, and 12 keywords were combined, concluding with the selection of 38 articles. Sources of risk of bias were assessed regarding randomisation procedures, selective outcome reporting and generalisability of results. Assessment procedures involving non-invasive methods applied with health and safety-related goals were filtered. Working-age participants from homogeneous occupational groups were selected, with these groups primarily including firefighters and construction workers. Research objectives were mainly directed to assess heat stress and physiological workload demands. Heart rate related variables, thermal responses and motion tracking through accelerometry were the most common approaches. Overall, wearable sensors proved to be valid tools for assessing physiological status in working environments. Future research should focus on conducting sensor fusion assessments, engaging wearables in real-time evaluation methods and giving continuous feedback to workers and practitioners.

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Section: Other Monitored Variablesmentioning

confidence: 99%

Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review

Bustos

Guedes

Baptista

et al. 2021

Sensors

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“…using recent advances in piezoelectric technology by harvesting energy from biomechanical movement [ 27 , 85 ]. The wearables can also be extended to smart prosthetics and other assistive technologies [ 86 ].…”

Section: General Applicationsmentioning

confidence: 99%

Artificial Intelligence Based Body Sensor Network Framework—Narrative Review: Proposing an End-to-End Framework using Wearable Sensors, Real-Time Location Systems and Artificial Intelligence/Machine Learning Algorithms for Data Collection, Data Mining and Knowledge Discovery in Sports and Healthcare

et al. 2021

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With the rising amount of data in the sports and health sectors, a plethora of applications using big data mining have become possible. Multiple frameworks have been proposed to mine, store, preprocess, and analyze physiological vitals data using artificial intelligence and machine learning algorithms. Comparatively, less research has been done to collect potentially high volume, high-quality ‘big data’ in an organized, time-synchronized, and holistic manner to solve similar problems in multiple fields. Although a large number of data collection devices exist in the form of sensors. They are either highly specialized, univariate and fragmented in nature or exist in a lab setting. The current study aims to propose artificial intelligence-based body sensor network framework (AIBSNF), a framework for strategic use of body sensor networks (BSN), which combines with real-time location system (RTLS) and wearable biosensors to collect multivariate, low noise, and high-fidelity data. This facilitates gathering of time-synchronized location and physiological vitals data, which allows artificial intelligence and machine learning (AI/ML)-based time series analysis. The study gives a brief overview of wearable sensor technology, RTLS, and provides use cases of AI/ML algorithms in the field of sensor fusion. The study also elaborates sample scenarios using a specific sensor network consisting of pressure sensors (insoles), accelerometers, gyroscopes, ECG, EMG, and RTLS position detectors for particular applications in the field of health care and sports. The AIBSNF may provide a solid blueprint for conducting research and development, forming a smooth end-to-end pipeline from data collection using BSN, RTLS and final stage analytics based on AI/ML algorithms.

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“…Furthermore to speedup positive changes, the trainings could be performed twice a day to improve fatigue resistance and cardio-respiratory reserve. 28,29 Wearable devices are an emerging and cost-effective technology that allows to monitor several biometric data, 30 and have been tested in many diseases. 31 It might be interesting to add one of these devices (e.g.…”

Section: Suggested Workoutmentioning

confidence: 99%

To contrast and reverse skeletal muscle weakness by Full-Body In-Bed Gym in chronic COVID-19 pandemic syndrome

et al. 2021

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Mobility-impaired persons, either very old or younger but suffering with systemic neuromuscular disorders or chronic organ failures, spend small amounts of time for daily physical activity, contributing to aggravate their poor mobility by resting muscle atrophy. Sooner or later the limitations to their mobility enforce them to bed and to more frequent hospitalizations. We include among these patients at risk those who are negative for the SARS-COV-2 infection, but suffering with COVID-19 pandemic syndrome. Beside managements of psychological symptoms, it is mandatory to offer to the last group physical rehabilitation approaches easy to learn and self-managed at home. Inspired by the proven capability to recover skeletal muscle contractility and strength by home-based volitional exercises and functional electrical stimulation, we suggest also for chronic COVID-19 pandemic syndrome a 10–20 min long daily routine of easy and safe physical exercises that can activate, and recover from weakness, the main 400 skeletal muscles used for every-day mobility activities. Persons can do many of them in bed (Full-Body in-Bed Gym), and hospitalized patients can learn this light training before leaving the hospital. It is, indeed, an extension of well-established cardiovascular-respiratory rehabilitation training performed after heavy surgical interventions. Blood pressure readings, monitored before and after daily routine, demonstrate a transient decrease in peripheral resistance due to increased blood flow of many muscles. Continued regularly, Full-Body in-Bed Gym may help maintaining independence of frail people, including those suffering with the COVID-19 pandemic syndrome.

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Wearable sensors: At the frontier of personalised health monitoring, smart prosthetics and assistive technologies

Cited by 128 publications

References 178 publications

Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review

Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review

To contrast and reverse skeletal muscle weakness by Full-Body In-Bed Gym in chronic COVID-19 pandemic syndrome

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