Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch

DM Burns, N Leung, M Hardisty… - Physiological …, 2018 - iopscience.iop.org
Objective: Participation in a physical therapy program is considered one of the greatest
predictors of successful conservative management of common shoulder disorders. However …

Adherence monitoring of rehabilitation exercise with inertial sensors: A clinical validation study

L Bavan, K Surmacz, D Beard, S Mellon, J Rees - Gait & posture, 2019 - Elsevier
Background Rehabilitation has an established role in the management of a wide range of
musculoskeletal conditions. Much of this treatment relies on self-directed exercises at home …

[HTML][HTML] Adherence patterns and dose response of physiotherapy for rotator cuff pathology: longitudinal cohort study

D Burns, P Boyer, H Razmjou, R Richards… - JMIR rehabilitation and …, 2021 - rehab.jmir.org
Background Physiotherapy is considered to be essential for the successful operative and
nonoperative management of rotator cuff pathology; however, the extent to which patients …

Supervised machine learning applied to wearable sensor data can accurately classify functional fitness exercises within a continuous workout

E Preatoni, S Nodari, NF Lopomo - Frontiers in Bioengineering and …, 2020 - frontiersin.org
Observing, classifying and assessing human movements is important in many applied fields,
including human-computer interface, clinical assessment, activity monitoring and sports …

Ensemble methods for classification of physical activities from wrist accelerometry

AK Chowdhury, D Tjondronegoro… - … and science in …, 2017 - eprints.qut.edu.au
PURPOSE To investigate whether the use of ensemble learning algorithms improve
physical activity recognition accuracy compared to the single classifier algorithms, and to …

Wearable sensors and smart devices to monitor rehabilitation parameters and sports performance: an overview

R De Fazio, VM Mastronardi, M De Vittorio, P Visconti - Sensors, 2023 - mdpi.com
A quantitative evaluation of kinetic parameters, the joint's range of motion, heart rate, and
breathing rate, can be employed in sports performance tracking and rehabilitation …

An activity recognition model using inertial sensor nodes in a wireless sensor network for frozen shoulder rehabilitation exercises

HC Lin, SY Chiang, K Lee, YC Kan - Sensors, 2015 - mdpi.com
This paper proposes a model for recognizing motions performed during rehabilitation
exercises for frozen shoulder conditions. The model consists of wearable wireless sensor …

Motor Ingredients Derived from a Wearable Sensor‐Based Virtual Reality System for Frozen Shoulder Rehabilitation

SH Lee, SC Yeh, RC Chan, S Chen… - BioMed research …, 2016 - Wiley Online Library
Objective. This study aims to extract motor ingredients through data mining from wearable
sensors in a virtual reality goal‐directed shoulder rehabilitation (GDSR) system and to …

User-independent recognition of sports activities from a single wrist-worn accelerometer: A template-matching-based approach

J Margarito, R Helaoui, AM Bianchi… - IEEE Transactions …, 2015 - ieeexplore.ieee.org
Goal: To investigate the accuracy of template matching for classifying sports activities using
the acceleration signal recorded with a wearable sensor. Methods: A population of 29 …

Evaluation of machine learning models for classifying upper extremity exercises using inertial measurement unit-based kinematic data

A Hua, P Chaudhari, N Johnson… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
The amount of home-based exercise prescribed by a physical therapist is difficult to monitor.
However, the integration of wearable inertial measurement unit (IMU) devices can aid in …