PhysioEdge: Multimodal Compressive Sensing Platform for Wearable Health Monitoring
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866909682748096512 |
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| author | Baeyens, Rens Laurijssen, Dennis Steckel, Jan Daems, Walter |
| author_facet | Baeyens, Rens Laurijssen, Dennis Steckel, Jan Daems, Walter |
| contents | The integration of compressive sensing with real-time embedded systems opens new possibilities for efficient, low-power biomedical signal acquisition. This paper presents a custom hardware platform based on the RP2350 micro-controller, tailored for synchronized multi-modal biomedical monitoring. The system is capable of capturing cardiopulmonary sounds, along with biopotential signals such as phonocardiography (PCG), electrocardiography (ECG) and electromyography (EMG), photoplethysmography (PPG), and inertial measurement unit (IMU) data for posture recognition. To ensure sample-accurate synchronization, a Sub-1GHz radio system is used across multiple nodes. Wi-Fi and Bluetooth connectivity enable centralized data aggregation. Experimental results demonstrate the achieved decrease in power consumption when using compressive sensing, efficient multi-node synchronization, and scalability for wireless biomedical monitoring applications. The compact form factor and low-cost design make it suitable for various medical applications, including remote healthcare and long-term monitoring. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_07645 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PhysioEdge: Multimodal Compressive Sensing Platform for Wearable Health Monitoring Baeyens, Rens Laurijssen, Dennis Steckel, Jan Daems, Walter Systems and Control The integration of compressive sensing with real-time embedded systems opens new possibilities for efficient, low-power biomedical signal acquisition. This paper presents a custom hardware platform based on the RP2350 micro-controller, tailored for synchronized multi-modal biomedical monitoring. The system is capable of capturing cardiopulmonary sounds, along with biopotential signals such as phonocardiography (PCG), electrocardiography (ECG) and electromyography (EMG), photoplethysmography (PPG), and inertial measurement unit (IMU) data for posture recognition. To ensure sample-accurate synchronization, a Sub-1GHz radio system is used across multiple nodes. Wi-Fi and Bluetooth connectivity enable centralized data aggregation. Experimental results demonstrate the achieved decrease in power consumption when using compressive sensing, efficient multi-node synchronization, and scalability for wireless biomedical monitoring applications. The compact form factor and low-cost design make it suitable for various medical applications, including remote healthcare and long-term monitoring. |
| title | PhysioEdge: Multimodal Compressive Sensing Platform for Wearable Health Monitoring |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2507.07645 |