Wearable technologies for active living and rehabilitation: Current research challenges and future opportunities

Rodgers, Mary M.; Alon, Gad; Pai, Vinay M.; Conroy, Richard

doi:10.1177/2055668319839607

Cited by 72 publications

(65 citation statements)

References 68 publications

(73 reference statements)

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“…Wearable technology is facing a variety of challenges in evaluating designs and algorithms, human-centred design, and personalisation 32 , 33 . We believe that our methodology can provide a major step towards rapid and systematic design exploration, including software and hardware, as well as system personalisation.…”

Section: Discussionmentioning

confidence: 99%

Estimating wearable motion sensor performance from personal biomechanical models and sensor data synthesis

Derungs

Amft

2020

Sci Rep

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We present a fundamentally new approach to design and assess wearable motion systems based on biomechanical simulation and sensor data synthesis. We devise a methodology of personal biomechanical models and virtually attach sensor models to body parts, including sensor positions frequently considered for wearable devices. The simulation enables us to synthesise motion sensor data, which is subsequently considered as input for gait marker estimation algorithms. We evaluated our methodology in two case studies, including running athletes and hemiparetic patients. Our analysis shows that running speed affects gait marker estimation performance. Estimation error of stride duration varies between athletes across 834 simulated sensor positions and can soar up to 54%, i.e. 404 ms. In walking patients after stroke, we show that gait marker performance differs between affected and less-affected body sides and optimal sensor positions change over a period of movement therapy intervention. For both case studies, we observe that optimal gait marker estimation performance benefits from personally selected sensor positions and robust algorithms. Our methodology enables wearable designers and algorithm developers to rapidly analyse the design options and create personalised systems where needed, e.g. for patients with movement disorders.

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Section: Discussionmentioning

confidence: 99%

Estimating wearable motion sensor performance from personal biomechanical models and sensor data synthesis

Derungs

Amft

2020

Sci Rep

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“…Through sensor technology, wearable health devices can collect all kinds of user information, such as health information, geographical location, and living habits [34]. The various formats, large scale, and numerous mobile links of these data may increase the risk of leakage and tampering [8,35,122,123].…”

Section: Security and Privacy Concernsmentioning

confidence: 99%

“…There are many technical bottlenecks in the applications of wearable medical devices [64,124,125]: (1) Data accuracy [9,24,118,122]: On one hand, the sensor specificity of current wearable device is low, which may lead to overdetection of benign nonclinical related signals, resulting in misdiagnosis, unnecessary examinations, and patient anxiety. On the other hand, low sensor sensitivity may lead to omission of pathological clinically-relevant parameters, resulting in missed diagnosis and delay in treatment.…”

Section: Technological Barriersmentioning

confidence: 99%

Wearable Health Devices in Health Care: Narrative Systematic Review (Preprint)

Lu¹,

Zhang²,

Xie³

et al. 2020

Preprint

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UNSTRUCTURED With the development of science and technology, wearable devices have been widely used in the field of health care. In this article, we summarize the characteristics, key technologies, and classification of wearable devices, as well as their application in health and safety monitoring, chronic disease management, diagnosis and treatment of diseases, and rehabilitation. We analyze the shortcomings of wearable devices to highlight development trends and provide a useful reference for the development of wearable devices by collecting data on the application and investigation of wearable devices in the medical field.

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“…All this information, correlated with medical data, significantly contributes to the overall picture of the cumulative effect of exposure to environmental factors. Wearable monitoring systems may provide a solution in promoting wellness management and rehabilitation outside clinical environments, when used as smart sensor nodes integrated into a portable device with a reasonably small form factor, that does not hinder or limit the individual’s activity [ 42 ].…”

Section: Introductionmentioning

confidence: 99%

A New Hybrid Sensitive PANI/SWCNT/Ferrocene-Based Layer for a Wearable CO Sensor

Savin

Mihailescu

Avramescu

et al. 2021

Sensors

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Developing a sensing layer with high electroactive properties is an important aspect for proper functionality of a wearable sensor. The polymeric nanocomposite material obtained by a simple electropolymerization on gold interdigitated electrodes (IDEs) can be optimized to have suitable conductive properties to be used with direct current (DC) measurements. A new layer based on polyaniline:poly(4-styrenesulfonate) (PANI:PSS)/single-walled carbon nanotubes (SWCNT)/ferrocene (Fc) was electrosynthesized and deposed on interdigital transducers (IDT) and was characterized in detail using electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), scanning electron microscopy (SEM), Raman spectroscopy, X-ray photoemission spectroscopy (XPS), and X-ray diffraction (XRD). The sensor characteristics of the material towards carbon monoxide (CO) in the concentration range of 10–300 ppm were examined, showing a minimal relative humidity interference of only 1% and an increase of sensitivity with the increase of CO concentration. Humidity interference could be controlled by the number of CV cycles when a compact layer was formed and the addition of Fc played an important role in the decrease of humidity. The results for CO detection can be substantially improved by optimizing the number of deposition cycles and enhancing the Fc concentration. The material was developed for selective detection of CO in real environmental conditions and shows good potential for use in a wearable sensor.

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Wearable technologies for active living and rehabilitation: Current research challenges and future opportunities

Cited by 72 publications

References 68 publications

Estimating wearable motion sensor performance from personal biomechanical models and sensor data synthesis

Estimating wearable motion sensor performance from personal biomechanical models and sensor data synthesis

Wearable Health Devices in Health Care: Narrative Systematic Review (Preprint)

A New Hybrid Sensitive PANI/SWCNT/Ferrocene-Based Layer for a Wearable CO Sensor

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