Dedicated cardiac rehabilitation wearable sensor and its clinical potential

Abstract

We describe a wearable sensor developed for cardiac rehabilitation (CR) exercise. To effectively guide CR exercise, the dedicated CR wearable sensor (DCRW) automatically recommends the exercise intensity to the patient by comparing heart rate (HR) measured in real time with a predefined target heart rate zone (THZ) during exercise. The CR exercise includes three periods: pre-exercise, exercise with intensity guidance, and post-exercise. In the pre-exercise period, information such as THZ, exercise type, exercise stage order, and duration of each stage are set up through a smartphone application we developed for iPhones and Android devices. The set-up information is transmitted to the DCRW via Bluetooth communication. In the period of exercise with intensity guidance, the DCRW continuously estimates HR using a reflected pulse signal in the wrist. To achieve accurate HR measurements, we used multichannel photo sensors and increased the chances of acquiring a clean signal. Subsequently, we used singular value decomposition (SVD) for de-noising. For the median and variance of RMSEs in the measured HRs, our proposed method with DCRW provided lower values than those from a single channel-based method and template-based multiple-channel method for the entire exercise stage. In the post-exercise period, the DCRW transmits all the measured HR data to the smartphone application via Bluetooth communication, and the patient can monitor his/her own exercise history.

Fig 1. System for cardiac rehabilitation exercises using DCRW with a smartphone application.

Fig 2. Pre-exercise stage with the cardiac rehabilitation (CR) application.

(a) main menu, (b) exercise and THZ set-up, (c) THZ set-up (d) exercise type, exercise stage order, and duration of each stage.

Fig 3. The DCRW front face.

Fig 4. Middle LED part providing information on exercise stage.

(a) before starting exercise or during rest (b) warm-up or cool-down stage (c) main exercise stage.

Fig 5. Side LEDs for exercise intensity guidance.

(a) pace down (HR is greater than THZ), (b) pace up (HR is less than THZ), (c) keep the pace (HR is within THZ).

Fig 6. Post-exercise stage with the cardiac rehabilitation (CR) application.

(a) exercise history summary, (b) calendar-based exercise history, (c) exercise analysis, (d) heart rate trace example in warm-up stage, (e) heart rate example in main exercise stage.

Fig 7. DCRW bottom view.

Fig 8. Internal system block diagram of the DCRW.

Fig 9. Multichannel pulse signal measured from DCRW and its singular decomposition value-based decomposed signals (channels 1 to 5 from left to right).

(a) measured multichannel pulse signals, (b) decomposed signals u₁σ₁v₁^T, (c) decomposed signals u₂σ₂v₂^T, (d) decomposed signals u₃σ₃v₃^T, (e) decomposed signals u₄σ₄v₄^T, (f) decomposed signals u₅σ₅v₅^T.

Fig 10. RMSEs distribution of the single-channel method, multiple channel-based template update method, and the proposed method with our DCRW.

(a) walking (warm-up), (b) jogging (main exercise), (c) walking (rest), (d) additional jogging (main exercise) and (e) walking (cool-down). The diamonds above and below represent the 5^th and 95^th percentiles of each group, and the squares above and below represent the 90^th and 10^th percentiles. Whiskers above and below indicate the 75^th and 25^th percentiles, respectively. The circle is the median value.

Fig 11. Individual HR traces obtained with the Holter monitor and DCRW during exercise.

(a) subject #1, (b) subject #2, (c) subject #3, (d) subject #4, (e) subject #5, (f) subject #6.