Carlos Barbosa Rodrigues

Abstract
This study applies phase plane analysis of medio-lateral, anteroposterior, and vertical directions for the coordination assessment of whole-body (WB) center of mass (COM) movement during the impulse phase of a standard maximum vertical jump (MVJ) with long, short, and no countermovement (CM). A video system and force platform were used, with the amplitudes of WB COM excursion obtained from image-based motion capture at each anatomical direction, and the 2D and 3D mean radial distance were compared under long, short, and no CM conditions. The estimate of the population mean length was used as a measure of distribution concentration, and the Rayleigh statistical test for circular data was applied with the sample distribution critical value. Watson’s U2 goodness-of-fit test for the von Mises distribution was used with the mean direction and concentration factor. The applied metrics led to the detection of shared and specific features in the global and phase plane analysis of WB COM movement coordination in the medio-lateral, anteroposterior, and vertical directions during long, short, and no CM conditions in relation to MVJ performance assessed from ground reaction force (GRF) through the force platform. Thus, long, short, and no CM impulses share lower amplitudes of WB COM excursion in the medio-lateral direction and mean radial distance to its mean, whereas the anteroposterior and vertical excursion of WB COM, along with the 2D transversal and 3D spatial length of the WB COM path, present as potential predictors of MVJ performance, with distinct behavior in long CM compared to short and no CM. Additionally, the applied workflow on generalized phase plane analysis led to the detection, through complementary metrics, of the anatomical WB COM movement directions with higher coordination based on phase concentration tests at 5% significance, in line with MVJ performance under different CM conditions. © 2026 by the authors.

Abstract

Abstract

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.