A novel device based on smart textile to control heart's activity during exercise

Area of Science:

• Cardiology
• Biomedical Engineering
• Sports Science

Background:

• Advancements in wearable technology have led to systems for monitoring cardiac function during exercise.
• Some systems record RR data for heart rate variability (HRV) analysis, crucial for assessing cardiac autonomic function.
• Comparing novel wearable systems with traditional medical devices is essential for validating their clinical utility.

Purpose of the Study:

• To compare RR interval data and HRV parameters between a smart textile system (GOW) and a hospital-grade electrocardiogram (ECG) machine.
• To evaluate the accuracy and reliability of the GOW system for both heart rate (HR) monitoring and HRV analysis during exercise.

Main Methods:

• Twelve cardiology patients underwent a 30-minute continuous cycling test at a stable submaximal intensity.
• Simultaneous RR interval data were collected using the GOW smart textile system and a standard ECG machine.
• Statistical analyses, including Bland-Altman analyses and intraclass correlation coefficients, were performed on 3-minute RR segments.

Main Results:

• The GOW system demonstrated stable limits of agreement (LoAs) for RR intervals, averaging around 3 ms, indicating good accuracy for beat-to-beat timing.
• However, HRV parameters, particularly those reflecting short-term changes (RMSSD, HF, SD1), exhibited wide LoAs, suggesting significant measurement error.
• The GOW system's accuracy for HRV metrics was compromised, likely due to inherent system measurement errors.

Conclusions:

• The GOW smart textile system is validated as a reliable tool for controlling and monitoring heart rate (HR) during physical activity.
• The system's limitations in accurately measuring HRV parameters preclude its use as a clinical tool for detailed cardiac autonomic function assessment.
• Further research and system improvements are needed to enhance the accuracy of wearable sensors for comprehensive HRV analysis in clinical settings.