Artificial intelligence and machine learning| applications in musculoskeletal physiotherapy

C Tack - Musculoskeletal Science and Practice, 2019 - Elsevier
Introduction Artificial intelligence (AI) is a field of mathematical engineering which has
potential to enhance healthcare through new care delivery strategies, informed decision …

A review of computational approaches for evaluation of rehabilitation exercises

Y Liao, A Vakanski, M Xian, D Paul, R Baker - Computers in biology and …, 2020 - Elsevier
Recent advances in data analytics and computer-aided diagnostics stimulate the vision of
patient-centric precision healthcare, where treatment plans are customized based on the …

Wearable systems for shoulder kinematics assessment: A systematic review

A Carnevale, UG Longo, E Schena… - BMC musculoskeletal …, 2019 - Springer
Background Wearable sensors are acquiring more and more influence in diagnostic and
rehabilitation field to assess motor abilities of people with neurological or musculoskeletal …

Recognition and repetition counting for complex physical exercises with deep learning

A Soro, G Brunner, S Tanner, R Wattenhofer - Sensors, 2019 - mdpi.com
Activity recognition using off-the-shelf smartwatches is an important problem in human
activity recognition. In this paper, we present an end-to-end deep learning approach, able to …

Home-based rehabilitation of the shoulder using auxiliary systems and artificial intelligence: an overview

B Cunha, R Ferreira, ASP Sousa - Sensors, 2023 - mdpi.com
Advancements in modern medicine have bolstered the usage of home-based rehabilitation
services for patients, particularly those recovering from diseases or conditions that …

Applications of wearable sensors in upper extremity MSK conditions: a scoping review

SM Zadeh, J MacDermid, J Johnson… - Journal of …, 2023 - Springer
Purpose This scoping review uniquely aims to map the current state of the literature on the
applications of wearable sensors in people with or at risk of developing upper extremity …

Physiotherapy exercise classification with single-camera pose detection and machine learning

C Arrowsmith, D Burns, T Mak, M Hardisty, C Whyne - Sensors, 2022 - mdpi.com
Access to healthcare, including physiotherapy, is increasingly occurring through virtual
formats. At-home adherence to physical therapy programs is often poor and few tools exist to …

Digitally assisted versus conventional home-based rehabilitation after arthroscopic rotator cuff repair: a randomized controlled trial

FD Correia, M Molinos, S Luís, D Carvalho… - American journal of …, 2022 - journals.lww.com
Objective The aim of this study was to evaluate the clinical impact of a 12-wk home-based
digitally assisted rehabilitation program after arthroscopic rotator cuff repair against …

The role of artificial intelligence in future rehabilitation services: a systematic literature review

C Mennella, U Maniscalco, G De Pietro… - IEEE Access, 2023 - ieeexplore.ieee.org
Artificial intelligence technologies are considered crucial in supporting a decentralized
model of care in which therapeutic interventions are provided from a distance. In the last …

Asynchronous and tailored digital rehabilitation of chronic shoulder pain: a prospective longitudinal cohort study

D Janela, F Costa, M Molinos, RG Moulder… - Journal of Pain …, 2022 - Taylor & Francis
Background Chronic shoulder pain (SP) is responsible for significant morbidity, decreased
quality of life and impaired work ability, resulting in high socioeconomic burden. Successful …