A Non-Invasive Multichannel Hybrid Fiber-Optic Sensor System for Vital Sign Monitoring

Fajkus, Marcel; Nedoma, Jan; Martínek, Radek; Vašinek, Vladimír; Nazeran, Homer; Šiška, Petr

doi:10.3390/s17010111

Cited by 134 publications

(89 citation statements)

References 42 publications

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“…By using a suitable encapsulation, it is possible to implement a sensor of almost any physical quantity. FBG sensors are used in automobile [18] and railway transport [19], the construction industry [20], power engineering, biomedical [21] or perimetric applications [22], etc.…”

Section: Fiber Bragg Grating Sensor Using For Recognition Of Number Omentioning

confidence: 99%

Design of a New Method for Detection of Occupancy in the Smart Home Using an FBG Sensor

Vaňuš¹,

Nedoma²,

Fajkus³

et al. 2020

Preprint

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This article introduces a new way of using a Fibre Bragg Grating (FBG) sensor for detecting the presence and number of occupants in the monitored space in a Smart Home (SH). CO2 sensors are used to determine the CO2 concentration of the monitored rooms in an SH. CO2 sensors can also be used for occupancy recognition of the monitored spaces in SH. To determine the presence of occupants in the monitored rooms of the SH, the newly devised method of CO2 prediction, by means of an Artificial Neural Network (ANN) with a Scaled Conjugate Gradient (SCG) algorithm using measurements of typical operational technical quantities (indoor temperature, relative humidity indoor and CO2 concentration in the SH) is used. The goal of the experiments is to verify the possibility of using the FBG sensor in order to unambiguously detect the number of occupants in the selected room (R104) and, at the same time, to harness the newly proposed method of CO2 prediction with ANN SCG for recognition of the SH occupancy status and the SH spatial location (rooms R104, R203, and R204) of an occupant. The designed experiments will verify the possibility of using a minimum number of sensors for measuring the non-electric quantities of indoor temperature and indoor relative humidity and the possibility of monitoring the presence of occupants in the SH using CO2 prediction by means of the ANN SCG method with ANN learning for the data obtained from only one room (R203). The prediction accuracy exceeded 90% in certain experiments. The uniqueness and innovativeness of the described solution lie in the integrated multidisciplinary application of technological procedures (the BACnet technology control SH, FBG sensors) and mathematical methods (ANN prediction with SCG algorithm, the Adaptive Filtration with of LMS algorithm) employed for the recognition of number persons and occupancy recognition of selected monitored rooms of SH.

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Section: Fiber Bragg Grating Sensor Using For Recognition Of Number Omentioning

confidence: 99%

Design of a New Method for Detection of Occupancy in the Smart Home Using an FBG Sensor

Vaňuš¹,

Nedoma²,

Fajkus³

et al. 2020

Preprint

Self Cite

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“…The authors in work [11] use fiber optic-based sensor with capability to measure up to 128 patients simultaneously. By using an integrated Sensor Device, their system can measure heart rate, respiratory rate, and temperature of patient.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, we give our conclusion in Section 5. Heart rate in [9,10,11,12], respiratory rate in [10,11,12], and temperature in [11,12] Support multiple patient monitoring Yes Yes in [11] Wireless data transmission ZigBee Bluetooth in [10] and Wi-Fi in [12] Monitoring interface PC PC in [9,11,12] and smartphone in [10]…”

Section: Introductionmentioning

confidence: 99%

Design of Wireless Vital Signs Monitoring System for Indoor Monitoring Activity

Daely¹,

Rizal²,

Hadiyoso³

2018

IJET

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Patient vital signs monitoring is an important activity in medical field, the situation in real medical facility usually does not allow for continuous monitoring. In a medical facility such as hospital or health care center, the patients outnumbered the staffs which makes it difficult to focus on each patient at a time. This problem can decrease chance to efficiently and effectively detecting medical condition. In this paper, we propose a wireless vital signs monitoring system, where multiple patients can be monitored at the same time. The system consists of two parts: Sensor Device to detect and measure patient's vital signs and Monitor Device to present the sensors' measurement result. We use ZigBee protocol for data transmission between devices. We compare our system to previous work to showcase the advantages of our work. We present the performance results related with the ZigBee communication and the display of Graphical User Interface (GUI). The results show that the system is capable of carrying out vital sign monitoring in indoor scenario with interactive measurement display that can help monitor multiple patients simultaneously.

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“…Therefore, these patients may need prompt first aid or transportation to the hospital. To meet this need, a vital signs monitoring system (VSMS) can be used to monitor patients using sensors, such as a heartbeat sensor (HB) and accelerometer sensor (ACC) [2] (for abbreviations, see Appendix A). HB and ACC sensors are used to measure heart rate (HR) and fall detection (FD), respectively.…”

Section: Introductionmentioning

confidence: 99%

An Autonomous Wireless Health Monitoring System Based on Heartbeat and Accelerometer Sensors

Fakhrulddin

Gharghan

2019

JSAN

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Falls are a main cause of injury for patients with certain diseases. Patients who wear health monitoring systems can go about daily activities without limitations, thereby enhancing their quality of life. In this paper, patient falls and heart rate were accurately detected and measured using two proposed algorithms. The first algorithm, abnormal heart rate detection (AHRD), improves patient heart rate measurement accuracy and distinguishes between normal and abnormal heart rate functions. The second algorithm, TB-AIC, combines an acceleration threshold and monitoring of patient activity/inactivity functions to accurately detect patient falls. The two algorithms were practically implemented in a proposed autonomous wireless health monitoring system (AWHMS). The AWHMS was implemented based on a GSM module, GPS, microcontroller, heartbeat and accelerometer sensors, and a smartphone. The measurement accuracy of the recorded heart rate was evaluated based on the mean absolute error, Bland–Altman plots, and correlation coefficients. Fourteen types of patient activities were considered (seven types of falling and seven types of daily activities) to determine the fall detection accuracy. The results indicate that the proposed AWHMS succeeded in monitoring the patient’s vital signs, with heart rate measurement and fall detection accuracies of 98.75% and 99.11%, respectively. In addition, the sensitivity and specificity of the fall detection algorithm (both 99.12%) were explored.

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A Non-Invasive Multichannel Hybrid Fiber-Optic Sensor System for Vital Sign Monitoring

Cited by 134 publications

References 42 publications

Design of a New Method for Detection of Occupancy in the Smart Home Using an FBG Sensor

Design of a New Method for Detection of Occupancy in the Smart Home Using an FBG Sensor

Design of Wireless Vital Signs Monitoring System for Indoor Monitoring Activity

An Autonomous Wireless Health Monitoring System Based on Heartbeat and Accelerometer Sensors

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