Projects.
MIMSunit: An open-source algorithm to compute movement summary from accelerometer
MIMS-unit is abbreviated for Monitor Independent Movement Summary unit. This measurement is developed to harmonize the processing of accelerometer data from different devices.
Posture and Physical Activity Detection: Impact of Number of Sensors and Feature Type
In this project, we evaluated the effect of single-site versus multisite motion sensing at seven body locations (both ankles, wrists, hips, and dominant thigh) on the detection of physical behavior recognition using a machine learning algorithm.
Signaligner Pro: A professional mobile sensor data visualization, annotation tool
Signaligner-Pro is an interactive tool for algorithm-assisted exploration and annotation of raw accelerometer data. The tool can be used by researchers using raw accelerometer data to support research in activity recognition/machine learning, exercise science, and sleep quality research among others.
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This paper describes an algorithm that automatically detects stereotypical motor movements (SMM) in individuals on the autism spectrum using three-axis accelerometer data obtained through wearable wireless sensors.
Automated Detection of Puffing and Smoking with Wrist Accelerometers
This project aims to detect puffing and smoking behavior in a real-world real-time or near-real-time setting with single or multiple on-body accelerometers.
Tower Airdrop: An Android Experimental Exergame for Kids to Motivate and Keep Them Sweater
The game incorporates simple motion primitives such as moving/shaking, tilting and touch gestures into different game tasks: triggering parachute, avoiding obstacles, and stacking a tower. The Game paces are designed to fit the focus attention of kids.