Wireless health monitoring system for ECG, EMG and EEG detecting

Nyni, K. A.; Vincent, Linson K; Varghese, Lisiya; Liya, V.L; Johny, Anil; Yesudas, C.V

doi:10.1109/iciiecs.2017.8275879

Cited by 10 publications

(10 citation statements)

References 6 publications

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“…For long-term monitoring purposes the considered frequency range may be reduced to 0.5–50 Hz and during the stress tests up to 30–50 Hz with a lower sampling frequency of 100 Hz. Conversely, the high-resolution ECG requires a wider frequency band, which is between

and 500 Hz [ 15 , 16 , 44 , 59 , 60 ].…”

Section: Electrocardiographymentioning

confidence: 99%

“…It takes approximately 100–120 ms. T waves reflect cardiac ventricular repolarization. Their amplitude ranges within values from 0.1–0.3 mV, the duration is 120–160 ms and the frequency at which it occurs varies from

to 7 Hz [ 15 , 59 , 60 ]. …”

Section: Electrocardiographymentioning

confidence: 99%

“…The HRV analysis is important not only for diagnosis of heart diseases, but also for detection of stroke, neuropathy related with diabetes mellitus or mental diseases. It is also an indispensable means of monitoring prenatal evolution, which helps to prevent neonatal mortality [ 15 , 17 , 60 ].…”

Section: Electrocardiographymentioning

confidence: 99%

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Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach—Part I: Cardiac Signals

Martínek

Ládrová

Šidiková

et al. 2021

Sensors

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Advanced signal processing methods are one of the fastest developing scientific and technical areas of biomedical engineering with increasing usage in current clinical practice. This paper presents an extensive literature review of the methods for the digital signal processing of cardiac bioelectrical signals that are commonly applied in today’s clinical practice. This work covers the definition of bioelectrical signals. It also covers to the extreme extent of classical and advanced approaches to the alleviation of noise contamination such as digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation and wavelet transform.

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and 500 Hz [ 15 , 16 , 44 , 59 , 60 ].…”

Section: Electrocardiographymentioning

confidence: 99%

to 7 Hz [ 15 , 59 , 60 ]. …”

Section: Electrocardiographymentioning

confidence: 99%

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Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach—Part I: Cardiac Signals

Martínek

Ládrová

Šidiková

et al. 2021

Sensors

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“…Many researchers detected different ions and obtained experiment data easier with wireless sensing system [5][6][7][8][9][10][11][12][13][14][15]. The wireless sensing system had been applied to different fields, such as chloride ion detection [5][6][7][8][9][10][11][12][13][14][15][16], hydrogen ion detection [17][18][19][20][21][22][23], glucose detection [23][24][25] and lactate detection [25].…”

Section: Introductionmentioning

confidence: 99%

“…The chloride sensors were applied to measure the chloride ion concentration for soil column, fluvarium and greenhouse. K. A. Nyni et al [9] developed the wireless health monitoring system for health monitoring, which contained the devices of the electro cardio gram (ECG), electroencephalogram (EEG) and electromyogram (EMG). They used the Arduino UNO board and Bluetooth module to construct the wireless transmission.…”

Section: Introductionmentioning

confidence: 99%

Sensing Characteristics of Arrayed Flexible Chloride Sensor Based on the XBee Wireless Sensing System

Tseng¹,

Wu²,

Chou³

et al. 2018

Preprint

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Water quality monitoring was an important objective in the surroundings. In this study, we investigated the sensing characteristics of the arrayed flexible chloride sensor with XBee wireless sensing system. The sensitivity and linearity of the wireless chloride sensing devices were 91.6 mV/pCl and 0.988, respectively. The hysteresis voltages were 50.14 mV and 36.71 mV during the cycles of 1 M → 10−1 M →   1 M → 10−3 M → 1 M and 1 M → 10−3 M → 1 M → 10−1 M → 1 M, respectively. The selectivity coefficients of the ClO− ion, ClO4− ion, NO3− ion and I− ion for Cl− ion were 5.0 × 10−2, 1.0 × 10−1, 5.9 × 10−3 and 5.6×10−1, respectively. The sensing characteristics of real time measurement were investigated for dynamic microfluidic. The arrayed flexible chloride sensor was integrated with the microfluidic device, syringe pump and wireless sensing system. The sensitivity and linearity were 273.1 mV/pCl and 0.978 at 35 μL/min, respectively.

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