Machine learning exercises follow a circular pattern. First, data is prepared and cleaned. Next, a data scientist will select an algorithm to use as the basis for the model. Then, a data scientist ...

This project focuses on the classification of physical activities using data collected from wearable sensors. The data was gathered using the Trivisio Colibri Wireless unit, which includes IMUs ...

Human activity detection from sensor data has developed as a critical study subject with far-reaching implications in healthcare, sports, security, and beyond. This study proposes a unique way to ...

This Python script integrates sensor data with quality control metrics to predict air quality using machine learning algorithms. It begins by loading and preprocessing data from CSV files, merging ...

We present approaches for gesture classification and gesture segmentation by using machine learning on the Kinect sensor's data stream. Our work involved three phases. Firstly we developed gesture ...

Low-cost, wearable sensors could increase access to care for patients with Parkinson's disease. New machine-learning approaches and a baseline of data from healthy older adults improve the ...

This study presents a non-invasive approach to detect anxiety and depression through gait analysis and machine learning, ...

Machine learning used to create a fabric-based touch sensor. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2024 / 04 / 240417182756.htm ...