Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities

E Halilaj, A Rajagopal, M Fiterau, JL Hicks… - Journal of …, 2018 - Elsevier
Traditional laboratory experiments, rehabilitation clinics, and wearable sensors offer
biomechanists a wealth of data on healthy and pathological movement. To harness the …

Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions

HF Nweke, YW Teh, G Mujtaba, MA Al-Garadi - Information Fusion, 2019 - Elsevier
Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …

Wearable movement sensors for rehabilitation: a focused review of technological and clinical advances

F Porciuncula, AV Roto, D Kumar, I Davis, S Roy… - Pm&r, 2018 - Elsevier
Recent technologic advancements have enabled the creation of portable, low-cost, and
unobtrusive sensors with tremendous potential to alter the clinical practice of rehabilitation …

Resolving the limb position effect in myoelectric pattern recognition

A Fougner, E Scheme, ADC Chan… - … on Neural Systems …, 2011 - ieeexplore.ieee.org
Reported studies on pattern recognition of electromyograms (EMG) for the control of
prosthetic devices traditionally focus on classification accuracy of signals recorded in a …

[HTML][HTML] Fall prediction and prevention systems: recent trends, challenges, and future research directions

R Rajagopalan, I Litvan, TP Jung - Sensors, 2017 - mdpi.com
Fall prediction is a multifaceted problem that involves complex interactions between
physiological, behavioral, and environmental factors. Existing fall detection and prediction …

The promise of mHealth: daily activity monitoring and outcome assessments by wearable sensors

BH Dobkin, A Dorsch - Neurorehabilitation and neural repair, 2011 - journals.sagepub.com
Mobile health tools that enable clinicians and researchers to monitor the type, quantity, and
quality of everyday activities of patients and trial participants have long been needed to …

[HTML][HTML] Application of data fusion techniques and technologies for wearable health monitoring

RC King, E Villeneuve, RJ White, RS Sherratt… - Medical engineering & …, 2017 - Elsevier
Technological advances in sensors and communications have enabled discrete integration
into everyday objects, both in the home and about the person. Information gathered by …

Multi-modal gait: A wearable, algorithm and data fusion approach for clinical and free-living assessment

Y Celik, S Stuart, WL Woo, E Sejdic, A Godfrey - Information Fusion, 2022 - Elsevier
Gait abnormalities are typically derived from neurological conditions or orthopaedic
problems and can cause severe consequences such as limited mobility and falls. Gait …

[HTML][HTML] Evaluation of feature extraction and recognition for activity monitoring and fall detection based on wearable sEMG sensors

X Xi, M Tang, SM Miran, Z Luo - Sensors, 2017 - mdpi.com
As an essential subfield of context awareness, activity awareness, especially daily activity
monitoring and fall detection, plays a significant role for elderly or frail people who need …

A framework for daily activity monitoring and fall detection based on surface electromyography and accelerometer signals

J Cheng, X Chen, M Shen - IEEE journal of biomedical and …, 2012 - ieeexplore.ieee.org
As an essential branch of context awareness, activity awareness, especially daily activity
monitoring and fall detection, is important to healthcare for the elderly and patients with …