Abstract
Wearable sensor technologies have emerged as a revolutionary technique for real-time monitoring of physiological parameters, particularly for healthcare applications. To guarantee their use, the sensors should be embedded in everyday equipment improving their wearability. In this context, the MAX30102 wearable sensor was studied and characterized for the monitoring of the PPG signal acquired on the index finger. Heart rate (HR), heart rate variability (HRV), and oxygen saturation (SpO2) measures were extracted from the PPG signal according to the pulse oximetry principles, by analysing the red and infrared signals detected by the LEDs embedded in the sensor. A valuation test was performed to compare the measures obtained by the MAX30102 with those achieved by two gold standard instruments used in clinical practices for cardiac and pulse oximetry measurements. The achieved results are promising, evidencing error rates lower than 2.5% for all the measures. The possibility to integrate such sensor in a ring-shaped device able to measure the vital parameters for health status monitoring can support the clinicians both in clinical and home settings for improving diagnosis, personalized treatments, and long-term monitoring.
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References
Collier R, Randolph AB, Collier R, Randolph AB (2015) Wearable technologies for healthcare innovation
Khan Y, Ostfeld AE, Lochner CM, Pierre A, Arias AC (2016) Monitoring of vital signs with flexible and wearable medical devices. https://doi.org/10.1002/adma.201504366
Lee H, Ko H, Lee J (2016) Reflectance pulse oximetry: practical issues and limitations ✩. ICT Express. 2:195–198. https://doi.org/10.1016/j.icte.2016.10.004
Fu Y, Liu J (2015) System design for wearable blood oxygen saturation and pulse measurement device 3:1187–1194. https://doi.org/10.1016/j.promfg.2015.07.197
Jeyhani V, Mahdiani S, Peltokangas M, Vehkaoja A (2015) Comparison of HRV parameters derived from photoplethysmography and electrocardiography signals. In: 37th annual international conference of the IEEE engineering in medicine and biology society, pp. 5952–5955. https://doi.org/10.1109/EMBC.2015.7319747
Liang T, Yuan YJ, Member S (2017) Wearable medical monitoring systems based on wireless networks: a review. IEEE Sens J 16:8186–8199. https://doi.org/10.1109/JSEN.2016.2597312
Turchetti BG, Micera S, Cavallo F, Odetti L, Dario P (2011) Technology and innovative services. IEEE Pulse 27–35
United Nations (2017) Department of Economic and Social Affairs, Population Division, World Aging Population 2017. https://doi.org/10.1049/el:20000788
Dias D, Cunha JPS (2018) Wearable health devices—vital sign monitoring, systems and technologies. Sensors (Switzerland) 18. https://doi.org/10.3390/s18082414
Izumi S, Yamashita K, Nakano M, Kawaguchi H, Marumoto K, Fuchikami T, Fujimori Y, Nakajima H, Shiga T, Yoshimoto M (2015) A wearable healthcare system with a 13.7 microA noise tolerant ECG processor. IEEE Trans Biomed Circuits Syst 9:733–742
Perego P, Standoli CE, Andreoni G (2015) Wearable monitoring of elderly in an ecologic setting: the SMARTA Project. https://doi.org/10.3390/ecsa-2-S3001
Pinheiro N, Couceiro R, Henriques J, Muehlsteff J, Quintal I, Goncalves L, Carvalho P (2016) Can PPG be used for HRV analysis? In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS, pp. 2945–2949. https://doi.org/10.1109/EMBC.2016.7591347
Betti S, Molino Lova R, Rovini E, Acerbi G, Santarelli L, Cabiati M, Del Ry S, Cavallo F (2017) Evaluation of an integrated system of wearable physiological sensors for stress monitoring in working environments by using biological markers. IEEE Trans Biomed Eng 9294. https://doi.org/10.1109/TBME.2017.2764507
Taelman J, Vandeput S, Spaepen A, Van Huffel S (2012) Influence of mental stress on heart rate and heart rate variability 37. https://doi.org/10.1007/978-3-642-23508-5
Orsila R, Virtanen M, Luukkaala T, Tarvainen M, Karjalainen P, Viik J, Savinainen M (2008) Perceived mental stress and reactions in heart rate variability—a pilot study among employees of an electronics company. Int J Occup Saf Ergon 14:275–283. https://doi.org/10.1080/10803548.2008.11076767
Picard RW, Healey JA (2013) Detecting stress during real-world driving tasks using physiological sensor. ProQuest Diss Theses 139. https://doi.org/10.1109/TITS.2005.848368
Fiorini L, Semeraro F, Mancioppi G, Betti S, Santarelli L, Cavallo F (2018) Physiological sensor system for the detection of human moods towards internet of robotic things applications. Front Artif Intell Appl 303:967–980. https://doi.org/10.3233/978-1-61499-900-3-967
Chalmers JA, Quintana DS, Abbott MJ-A, Kemp AH (2014) Anxiety disorders are associated with reduced heart rate variability: a meta-analysis. Front Psychiatry 5:80. https://doi.org/10.3389/fpsyt.2014.00080
Heart rate variability: a new way to track well-being—Harvard Health Blog—Harvard Health Publishing
Nitzan M, Romem A, Koppel R (2014) Pulse oximetry: fundamentals and technology update. Med Devices Evid Res 7:231–239. https://doi.org/10.2147/MDER.S47319
Lopez Silva SM, Dotor Castilla ML, Silveira Martin JP (2003) Near-infrared transmittance pulse oximetry with laser diodes. J Biomed Opt 8:525. https://doi.org/10.1117/1.1578495
Shao D, Liu C, Tsow F, Yang Y, Du Z, Iriya R, Yu H, Tao N (2016) Noncontact Monitoring of Blood Oxygen Saturation Using Camera and Dual-Wavelength Imaging System. IEEE Trans Biomed Eng 63:1091–1098. https://doi.org/10.1109/TBME.2015.2481896
Ma G, Zhu W, Zhong J, Tong T, Zhang J, Wang L (2018) Wearable ear blood oxygen saturation and pulse measurement system based on PPG. In: 2018 IEEE SmartWorld, ubiquitous intelligence and computing, advanced and trusted computing, scalable computing and communications, cloud and big data computing, internet of people and smart city innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, pp. 111–116. https://doi.org/10.1109/SmartWorld.2018.00054
Gima_Spa: Pulsoximetro da dito OXY-5, https://www.gimaitaly.com/prodotti.asp?sku=34282&dept_selected=620&dept_id=620
Casaccia S, Pietroni F, Calvaresi A, Revel GM, Scalise L (2016) Smart monitoring of user’s health at home: performance evaluation and signal processing of a wearable sensor for the measurement of heart rate and breathing rate 4:175–182. https://doi.org/10.5220/0005694901750182
Jarchi D, Casson A (2016) Description of a database containing wrist PPG signals recorded during physical exercise with both accelerometer and gyroscope measures of motion. Data 2:1. https://doi.org/10.3390/data2010001
Nweke HF, Teh YW, Mujtaba G, Al-garadi MA (2019) Data fusion and multiple classifier systems for human activity detection and health monitoring: review and open research directions. Inf Fusion 46:147–170. https://doi.org/10.1016/j.inffus.2018.06.002
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DAPHNE project funded by the Tuscany Region (PAR FAS 2007-2013, Bando FAS Salute 2014, CUP J52I16000170002)
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Fiorini, L., Cavallo, F., Martinelli, M., Rovini, E. (2021). Characterization of a PPG Wearable Sensor to Be Embedded into an Innovative Ring-Shaped Device for Healthcare Monitoring. In: Monteriù, A., Freddi, A., Longhi, S. (eds) Ambient Assisted Living. ForItAAL 2019. Lecture Notes in Electrical Engineering, vol 725. Springer, Cham. https://doi.org/10.1007/978-3-030-63107-9_5
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