Remote Monitoring of Tai Chi Balance Training Interventions in Older Adults Using Wearable Sensors and Machine Learning.

Tai Chi, an Asian martial art, is renowned for its health benefits, particularly in promoting healthy aging among older adults, improving balance, and reducing fall risk. However, methodological challenges hinder the objective measurement of adherence to and proficiency in performing a training protocol, critical for health outcomes. This study introduces a framework using wearable sensors and machine learning to monitor Tai Chi training adherence and proficiency.

Current State, Needs, and Opportunities for Wearable Robots in Military Medical Rehabilitation and Force Protection.

Despite advances in wearable robots across various fields, there is no consensus definition or design framework for the application of this technology in rehabilitation or musculoskeletal (MSK) injury prevention. This paper aims to define wearable robots and explore their applications and challenges for military rehabilitation and force protection for MSK injury prevention. We conducted a modified Delphi method, including a steering group and 14 panelists with 10+ years of expertise in wearable robots.

Wearable-Based Kinematic Analysis of Upper-Limb Movements During Daily Activities Could Provide Insights into Stroke Survivors' Motor Ability.

Background: Frequent and objective monitoring of motor recovery progression holds significant importance in stroke rehabilitation. Despite extensive studies on wearable solutions in this context, the focus has been predominantly on evaluating limb activity. This study aims to address this limitation by delving into a novel measure of wrist kinematics more intricately related to patients' motor capacity.

Position paper on how technology for human motion analysis and relevant clinical applications have evolved over the past decades: Striking a balance between accuracy and convenience.

Background: Over the past decades, tremendous technological advances have emerged in human motion analysis (HMA).

Research Question: How has technology for analysing human motion evolved over the past decades, and what clinical applications has it enabled?

Methods: The literature on HMA has been extensively reviewed, focusing on three main approaches: Fully-Instrumented Gait Analysis (FGA), Wearable Sensor Analysis (WSA), and Deep-Learning Video Analysis (DVA), considering both technical and clinical aspects.

Results: FGA techniques relying on data collected using stereophotogrammetric systems, force plates, and electromyographic sensors have been dramatically improved providing highly accurate estimates of the biomechanics of motion.

The role of NtrC in the adaptation of Herbaspirillum seropedicae SmR1 to nitrogen limitation and to nitrate.

The RNA-Seq profiling of Herbaspirillum seropedicae SmR1 wild-type and ntrC mutant was performed under aerobic and three nitrogen conditions (ammonium limitation, ammonium shock, and nitrate shock) to identify the major metabolic pathways modulated by these nitrogen sources and those dependent on NtrC. Under ammonium limitation, H. seropedicae scavenges nitrogen compounds by activating transporter systems and metabolic pathways to utilize different nitrogen sources and by increasing proteolysis, along with genes involved in carbon storage, cell protection, and redox balance, while downregulating those involved in energy metabolism and protein synthesis.