Carlos Barbosa Rodrigues

Abstract
During the COVID-19 pandemic, significant challenges arose in the on-site monitoring of patients’ clinical signs due to healthcare system overload, lack of resources, and the need for social distancing. These obstacles hindered readiness in identifying and responding promptly to cases, highlighting the importance of investments in healthcare infrastructure and technologies for effective monitoring in emergency situations. This study explores the use of a wearable, wireless, and scalable system for remote monitoring of physiotherapy sessions with an emphasis on applying human activity recognition. It employs a variety of sensors and equipment for the classification of physiotherapeutic exercises from a distance. The sensors and equipment provide data to a web platform that allows, for example, determining posture and classifying the activity performed by the patient through measuring the angulation between body limbs. This platform includes the design of wearable accessories, 3D-printed, portable, and wireless hardware construction. The web part consists of a remote server, a microservices environment including the provision of a web portal (https://bionet.ufpe.br) for user interaction, as well as data storage and processing, providing the information. Currently, a testing protocol is under development to be executed by volunteer physiotherapy specialists and their respective patients, with approval from the ethics committee (CAAE 71106023.0.0000.5208). © 2025 Elsevier B.V., All rights reserved.

Abstract
This study presents and applies time delay analysis of maximum cross-correlation between quadriceps and gastrocnemius sEMG neuromuscular control with lower limb joint angular coordination of the hip, the knee and the ankle joint angles, angular velocities and accelerations to assess long countermovement (CM) and stretch-shortening cycle (SSC) at countermovement jump (CMJ), short CM and SSC on drop jump (DJ), and no CM on squat jump (SJ), with different and shared features at each CM complementing functional anatomy analysis. © 2025 Elsevier B.V., All rights reserved.

Abstract

Abstract

Abstract
This study presents variability assessment of real time measurements from in-vivo internal joint loads with instrumented implant during post-operative (PO) recovery process from total hip arthroplasty on daily living gait activities. A total of 112 trials walking supported by crutches in both hands, contralateral and ipsilateral sides, walking on treadmill at constant velocities, accelerating, decelerating and free walking, were assessed from 9 different patients ranging 0.3 to 76-month PO. Variability was assessed based on standard deviation of the vertical joint load normalized to each subject body weight with this metric adequacy to monitor PO recover.