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Introduction:Seismocardiography (SCG) - measurements of cardiovascular-induced vibrations on the chest - has shown potential for providing clinical information for cardiac conditions. SCG is conventionally recorded by an accelerometer attached to a single point on chest. Recent research suggests multichannel SCG (mSCG) - measurements from multiple chest locations - can provide extra and more accurate clinical information. Current mSCG methods are limited to accelerometer arrays, laser Doppler vibrometry, and airborne ultrasound that are either costly, difficult for inexperienced users, or need bulky equipment, thereby impeding their use beyond research or clinical settings. Hypothesis:mSCG signals can be accurately estimated from tiny chest movements in chest videos recorded by ordinary cameras, e.g., those in smartphones. Methods:We enrolled 10 subjects (sbjs) with no history of CVDs (21.7 ± 1.7 years, 40% women). ECG and chest video of sbjs were recorded at rest for 15 sec during breath hold at the end of inhalation followed by another 15 sec recording during breath hold at the end of exhalation. We developed an AI-powered mobile app to record the chest videos and convert them to 0-30 Hz mSCG in right-to-left (RL) and head-to-foot (HF) directions (Fig 1a). Heart rate (HR) based on ECG RR interval and mSCG was measured and compared. Results:HR estimated from mSCG in both RL and HF directions had a good agreement with ECG-based HR using Bland-Altman analysis [RL: bias = 1.4 bpm, 95% CI = 5.6 bpm; HF: bias = 0.8 bpm, 95% CI = 6.2 bpm (Fig 1b)]. High-quality mSCG and ECG measurements were obtained for all sbjs. Conclusion:Clinically relevant information can be accurately extracted from chest videos using our novel, contactless, AI-based method. Given that the vast majority of Americans have access to a camera phone, future developments of this method may provide new means of remote and accessible cardiac monitoring.
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Physiological sensing on the upper arm with a wireless multi-modal wearable
In this research, we examine the potential of measuring physiological variables, including heart rate (HR) and respiration rate (RR) on the upper arm using a wireless multimodal sensing system consisting of an accelerometer, a gyroscope, a three-wavelength photoplethysmography (PPG), single-sided electrocardiography (SS-ECG), and bioimpedance (BioZ). The study included collecting HR data when the subject was at rest and typing, and RR data when the subject was at rest. The data from three wavelengths of PPG and BioZ were collected and compared to the SS-ECG as the standard. The accelerometer and gyro signals were used to exclude data with excessive noise due to motion. The results showed that when the subject remained sedentary, the mean absolute error (MAE) for the HR calculation for all three wavelengths of the PPG modality was less than two bpm, while the BioZ was 3.5 bpm compared with SS-ECG HR. The MAE for typing increased for both modalities and was less than three bpm for all three wavelengths of the PPG but increased to 7.5 bpm for the BioZ. Regarding RR, both modalities resulted in RR within one breath per minute of the SS-ECG modality for the one breathing rate. Overall, all modalities on this upper arm wearable worked well when the subject was sedentary. Still, the SS-ECG and PPG showed less variability for the HR signal in the presence of motion during micro-motions such as typing.
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- Award ID(s):
- 2037383
- PAR ID:
- 10533609
- Editor(s):
- Baba, Justin S; Coté, Gerard L
- Publisher / Repository:
- SPIE
- Date Published:
- ISBN:
- 9781510669598
- Page Range / eLocation ID:
- 26
- Format(s):
- Medium: X
- Location:
- San Francisco, United States
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1117/12.3003163
