A High-Performance, Secure Custom Electronics Circuit for Biopotential Measurement and Processing
-
Arrigo Palumbo
,
Barbara Calabrese
,
Nicola Ielpo
,
Remo Garropoli
,
Patrizia Vizza
,
Domenico Corchiola
,
Vera Gramigna
Abstract
Purpose: In this paper, we propose a secure wearable and portable device aiming to (i) monitor physical activity in medical and clinical rehabilitation, (ii) evaluate the subject's movements in sports environments, and (iii) monitor wellness indicators.
Materials and Methods: The innovative low-power custom circuit can acquire, pre-process, digitalize, and transmit EMG signals to a Raspberry PI4 device via a low-energy Bluetooth module. The Raspberry PI4 is a hub that sends data to a cloud-based system for remote monitoring and processing. The best cybersecurity practices have been implemented: firewall, anti-DDoS and SELinux.
Results: We have assessed the system's vulnerability before and after the system's hardening. SELinux makes the system safer and prevents unauthorized access to patients' data health by tampering with the devices.
Conclusion: Adopting IoT systems in telemedicine requires greater attention to cybersecurity. It is necessary to implement security mechanisms to guarantee the privacy of patient's health data.
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2- Wenbin Sun et al., "A Review of Recent Advances in Vital Signals Monitoring of Sports and Health via Flexible Wearable Sensors." Sensors, Vol. 22 (No. 20), p. 7784, (2022).
3- G. Yang et al., "IoT-Based Remote Pain Monitoring System: From Device to Cloud Platform." (in eng), IEEE J Biomed Health Inform, Vol. 22 (No. 6), pp. 1711-19, Nov (2018).
4- K. Katzis, L. Berbakov, G. Gardašević, and O. Šveljo, "Breaking Barriers in Emerging Biomedical Applications." (in eng), Entropy (Basel), Vol. 24 (No. 2), Jan 31 (2022).
5- H. Mrabet, S. Belguith, A. Alhomoud, and A. Jemai, "A Survey of IoT Security Based on a Layered Architecture of Sensing and Data Analysis." (in eng), Sensors (Basel, Switzerland), Vol. 20 (No. 13), Jun 28 (2020).
6- G. Fortino, A. Guerrieri, P. Pace, C. Savaglio, and G. Spezzano, "IoT Platforms and Security: An Analysis of the Leading Industrial/Commercial Solutions." (in eng), Sensors (Basel, Switzerland), Vol. 22 (No. 6), Mar 11 (2022).
7- Arrigo Palumbo, Patrizia Vizza, Barbara Calabrese, and Nicola Ielpo, "Biopotential Signal Monitoring Systems in Rehabilitation: A Review." Sensors, Vol. 21 (No. 21), p. 7172, (2021).
8- Lucas Medeiros Souza do Nascimento, Lucas Vacilotto Bonfati, Melissa La Banca Freitas, José Jair Alves Mendes Junior, Hugo Valadares Siqueira, and Sergio Luiz Stevan, "Sensors and Systems for Physical Rehabilitation and Health Monitoring—A Review." Sensors, Vol. 20 (No. 15), p. 4063, (2020).
9- S. Zhao et al., "Wearable Physiological Monitoring System Based on Electrocardiography and Electromyography for Upper Limb Rehabilitation Training." (in eng), Sensors (Basel, Switzerland), Vol. 20 (No. 17), Aug 28 (2020).
10- C. Wu, Y. Yan, Q. Cao, F. Fei, D. Yang, and A. Song, "A Low Cost Surface EMG Sensor Network for Hand Motion Recognition." in 2018 IEEE 1st International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS), (2018), pp. 35-39.
11- T. Uktveris and V. Jusas, "Development of a Modular Board for EEG Signal Acquisition." (in eng), Sensors (Basel, Switzerland), Vol. 18 (No. 7), Jul 3 (2018).
12- J. Mangal, "A Smart Wear based Portable Health Monitoring System." in 2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS), (2020), pp. 1-6.
13- Mohammed Al-khafajiy et al., "Remote health monitoring of elderly through wearable sensors." Multimedia Tools and Applications, Vol. 78 (No. 17), pp. 24681-706, 2019/09/01 (2019).
14- A. B. Jani, R. Bagree, and A. K. Roy, "Design of a low-power, low-cost ECG & EMG sensor for wearable biometric and medical application." in 2017 IEEE SENSORS, (2017), pp. 1-3.
15- Thanh Chau Nguyen, Tri-Quang Huynh, Tri-Thong Vo, Phuong Nam Nguyen, and Toi Vo Van, "An EEG Front-End System Using ADS1299." Singapore, (2018): Springer Singapore, pp. 717-22.
16- Arrigo Palumbo et al., "SIMpLE: A Mobile Cloud-Based System for Health Monitoring of People with ALS." Sensors, Vol. 21 (No. 21), p. 7239, (2021).
17- A. Palumbo, B. Calabrese, N. Ielpo, A. Demeco, A. Ammendolia, and D. Corchiola, "Cloud-based biomedical system for remote monitoring of ALS patients." in 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), (2020), pp. 1469-76.
18- A. Demeco et al., "Quantitative analysis of movements in facial nerve palsy with surface electromyography and kinematic analysis." Journal of Electromyography and Kinesiology, Vol. 56p. 102485, 2021/02/01/ (2021).
19- [Online]. Available: https://www.ti.com/product/INA126
20- [Online] Available: https://www.ti.com/lit/ds/symlink/ads1296r.pdf
21- [Online]. Available: https://www.ti.com/product/CC2640
22- [Online]. Available: https://developer.arm.com/Processors/Cortex-M3
23- [Online]. Available: https://www.szrfstar.com/product/144-en.html
24- [Online]. Available: https://www.ti.com/lit/ds/symlink/cc2640r2f.pdf?ts=1668003551888&ref_url=https%253A%252F%252Fwww.google.com%252F
25- [Online]. Available: https://www.ti.com/product/TPS61220
26- Alessandro de Sire et al., "Anterior Cruciate Ligament Injury Prevention Exercises: Could a Neuromuscular Warm-Up Improve Muscle Pre-Activation before a Soccer Game? A Proof-of-Principle Study on Professional Football Players." Applied Sciences, Vol. 11 (No. 11), p. 4958, (2021).
27- [Online]. Available: https://www.tenable.com/products/nessus
28- [Online]. Available: https://www.ti.com/product/BQ24232
| Files | ||
| Issue | Vol 11 No 3 (2024) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/fbt.v11i3.15881 | |
| Keywords | ||
| Telemonitoring Telerehabilitation Bio-Signal Acquisition Cybersecurity Electromyogram Internet of Things | ||
| Rights and permissions | |
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Palumbo A, Calabrese B, Ielpo N, Garropoli R, Vizza P, Corchiola D, Gramigna V. A High-Performance, Secure Custom Electronics Circuit for Biopotential Measurement and Processing. Frontiers Biomed Technol. 2024;11(3):361-374.
