Supporting data for “User-Centered Development and Validation of a Wearable Feedback System for Enhanced Fitness Training”
- Research Project Overview:
The research project focuses on the user-centered development and validation of a wearable feedback system designed to enhance fitness training. The system leverages Inertial Measurement Units (IMUs) to provide real-time feedback to users, guiding them to perform resistance training exercises (specifically squats and deadlifts exercises) at a constant speed and within a prescribed range of motion. The study aims to evaluate the effectiveness of this wearable feedback system by analyzing its impact on movement quality, muscle activation, and user motivation.
2. Sample Size and Target Participants:
Total Participants: 51 (28 males, 23 females).
Age Range: 19–67 years (median age: 25 years).
Target Participants: Individuals with varying levels of fitness experience, ranging from beginners to advanced trainees, to ensure the system's applicability across a broad user base.
3. Description of Data Files:
The dataset consists of the following types of data files, collected during supervised exercise sessions
(1) IMU Data Files:
Content: Time-series data from IMU sensors, including acceleration, angular velocity, and orientation of leg and trunk posision during squats and deadlfits exercises.
Purpose: To analyze movement kinematics, including speed, range of motion, and stability.
File Format: CSV, with columns for timestamp, sensor ID, and sensor measurements.
(2) EMG Data Files:
Content: Electromyography signals from lower back and limb muscles (e.g., quadriceps, glutes) recorded during exercises.
Purpose: To assess muscle activation patterns and compare amplitude changes with and without the wearable feedback system.
File Format: CSV or similar, with columns for timestamp, muscle group, and EMG signal amplitude.
(3) Voice Data Files:
Content: Audio recordings of participants' verbal feedback, interactions with researchers, and comments after exercises.
Purpose: To gather qualitative insights into user experience and perceived usability of the system.
File Format: Audio files (e.g., WAV or MP3).
