Acoustic BioPower Dataset: Physiological and Kinematic Signals During Weightlifting

Data from 24 healthy young adults performing bench press and squat exercises under acoustic biofeedback and generic music conditions. Physiological, kinetic, and kinematic signals were collected at 1000 Hz using wireless biosensors, and perceived enjoyment was rated via questionnaire. The dataset was created by Dania Furk and published on figshare under a CC-BY-4.0 license in May 2026.

Use Cases

• Analyzing the effect of acoustic biofeedback on power output based on force and kinematic data
• Correlating muscle activity (EMG) with movement acceleration (ACC) during resistance exercises
• Comparing physiological responses (ECG) between different auditory feedback conditions
• Modeling the relationship between exercise performance and self-reported enjoyment scores

Strengths

• Includes data from 24 participants (12 male, 12 female) with an average age of 22.2 ± 2.2 years
• Contains high-frequency (1000 Hz) time-series data for EMG, ECG, accelerometer, and force signals
• Covers two distinct exercises (bench press and squat) across multiple relative loads and three sessions
• Integrates physiological, kinetic, kinematic, and subjective (enjoyment) measurements

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Data may reflect geographic bias inherent to its collection at a single university in Portugal

Provenance

Source

Dania Furk via figshare

Collection Method

Experimental data collected using an 8-channel biosignalsplux wireless hub and Speediance GYM Monster 2 Digital Weight Machine.

Freshness

Last updated 2026-05-20 08:22:40

Geography

Data collected at Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, Portugal.