Quantification of Human Movement for Assessment in Automated Exercise Coaching

TL;DR

This paper presents a model-based approach using Kinect data to quantify human movement for automated exercise coaching, estimating strength and energy expenditure to assess performance improvements.

Contribution

It introduces a novel model-based assessment method combining biomechanical constraints with Kinect data for automated exercise evaluation.

Findings

Metrics showed trends consistent with improved performance for some subjects.

The approach estimates strength and energy expenditure from simple squatting exercises.

Demonstrates feasibility of automated movement assessment in home settings.

Abstract

Quantification of human movement is a challenge in many areas, ranging from physical therapy to robotics. We quantify of human movement for the purpose of providing automated exercise coaching in the home. We developed a model-based assessment and inference process that combines biomechanical constraints with movement assessment based on the Microsoft Kinect camera. To illustrate the approach, we quantify the performance of a simple squatting exercise using two model-based metrics that are related to strength and endurance, and provide an estimate of the strength and energy-expenditure of each exercise session. We look at data for 5 subjects, and show that for some subjects the metrics indicate a trend consistent with improved exercise performance.