Validity of an Automatic Approach for Acceleration Signal Segmentation during Weight Lifting

The increasing adoption of wearable sensors in biomechanics has enhanced the acquisition and analysis of physiological signals, enabling continuous real-time monitoring in naturalistic settings. In this context, automatic segmentation methods have emerged as efficient alternatives to manual segmentation, helping to overcome limitations such as time consumption and subjective variability. This study assessed the validity of an automatic segmentation approach for acceleration signals recorded d...

Bayesian Integrated Data Analysis and Experimental Design for External Magnetic Plasma Diagnostics in DEMO

A Novel Algorithm based on Ankle-Mounted IMU Configuration for Computing Spatiotemporal Parameters

Gait analysis plays a crucial role in understanding human locomotion, with applications in biomechanics, rehabilitation, and clinical diagnostics. Optical motion capture systems represent the gold standard in the field of gait analysis providing accurate information about human movement although they have the limit to be expensive, time-consuming and limited to the laboratory. Recently, wearable sensors, based mainly on inertial measurement units (IMUs), have emerged as a promising alternativ...

Virtual Reality and Biosignals for Labor Pain Relief: A Pilot Study

Labor pain is intense and multifaceted, requiring effective management to ensure both maternal and neonatal well-being. This study explores the use of virtual reality (VR) as a distraction tool, combined with biosignal monitoring. Electro-dermal activity and heart rate variability (HRV) were recorded using wearable devices on four pregnant women. The acquisition protocol was divided into three phases: before, during, and after VR exposure. To complement the physiological data, the Visual Anal...