scholarly journals A Power-Efficient Bio-Potential Acquisition Device with DS-MDE Sensors for Long-Term Healthcare Monitoring Applications

Sensors ◽  
2010 ◽  
Vol 10 (5) ◽  
pp. 4777-4793 ◽  
Author(s):  
Chia-Lin Chang ◽  
Chih-Wei Chang ◽  
Hong-Yi Huang ◽  
Chen-Ming Hsu ◽  
Chia-Hsuan Huang ◽  
...  
Keyword(s):  
Power Efficient ◽  
Monitoring Applications ◽  
Healthcare Monitoring ◽  
Acquisition Device

scholarly journals A High-Accuracy and Power-Efficient Self-Optimizing Wireless Water Level Monitoring IoT Device for Smart City

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1936
Author(s):  
Tsun-Kuang Chi ◽  
Hsiao-Chi Chen ◽  
Shih-Lun Chen ◽  
Patricia Angela R. Abu
Keyword(s):  
Power Consumption ◽  
Water Level ◽  
Smart City ◽  
High Accuracy ◽  
Control Device ◽  
Power Efficient ◽  
Sensor Module ◽  
Monitoring Applications ◽  
Level Monitoring ◽  
Water Level Monitoring

In this paper, a novel self-optimizing water level monitoring methodology is proposed for smart city applications. Considering system maintenance, the efficiency of power consumption and accuracy will be important for Internet of Things (IoT) devices and systems. A multi-step measurement mechanism and power self-charging process are proposed in this study for improving the efficiency of a device for water level monitoring applications. The proposed methodology improved accuracy by 0.16–0.39% by moving the sensor to estimate the distance relative to different locations. Additional power is generated by executing a multi-step measurement while the power self-optimizing process used dynamically adjusts the settings to balance the current of charging and discharging. The battery level can efficiently go over 50% in a stable charging simulation. These methodologies were successfully implemented using an embedded control device, an ultrasonic sensor module, a LORA transmission module, and a stepper motor. According to the experimental results, the proposed multi-step methodology has the benefits of high accuracy and efficient power consumption for water level monitoring applications.

Development of piezoresistive PDMS/MWCNT foam nanocomposite sensor with ultrahigh flexibility and compressibility

2021 ◽  
pp. 1045389X2110643
Author(s):  
Pardis Ghahramani ◽  
Kamran Behdinan ◽  
Hani E. Naguib
Keyword(s):  
Mechanical Properties ◽  
Mechanical Characteristics ◽  
Polymer Foam ◽  
Mwcnt Content ◽  
Mechanical Hysteresis ◽  
Electrical Hysteresis ◽  
Multi Walled Carbon Nanotube ◽  
Monitoring Applications ◽  
Healthcare Monitoring ◽  
High Flexibility

Polymer foam nanocomposites attract great interest in many wide ranges of biomedical and healthcare monitoring applications. In this study, we investigated the effect of porosity and multi-walled carbon nanotube (MWCNT) content on the piezoresistivity, sensitivity, and mechanical properties of Polydimethylsiloxane (PDMS)/MWCNT foam nanocomposite. The foam nanocomposites were fabricated by particulate leaching method and their electrical and mechanical characteristics were investigated using the different porosity levels (60% and 70%) and different conductive nanofiller contents (0.5 wt.% and 1 wt.%). The foam nanocomposites with 0.5 wt.% MWCNT content and 60% porosity possessed higher pressure sensitivity, higher gage factor, and lower electrical hysteresis along with higher mechanical properties. Moreover, fabricated PDMS/MWCNT foam nanocomposite demonstrated high flexibility, high compressibility, and high recoverability in addition to limited mechanical hysteresis (less than 3%) with a large dynamic sensing range. Contrary to the existing foam nanocomposite samples in the literature, PDMS/MWCNT foam nanocomposites withstood higher pressure ranges (3.5–5 MPa) at limited thickness (average 2.3 mm) without experiencing noticeable macroscopic damage.

scholarly journals An Investigation on the Sampling Frequency of the Upper-Limb Force Myographic Signals

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2432 ◽  
Author(s):  
Zhen Gang Xiao ◽  
Carlo Menon
Keyword(s):  
Upper Limb ◽  
Sampling Frequency ◽  
Isometric Actions ◽  
Monitoring Applications ◽  
Minimum Requirements ◽  
Data Content ◽  
Acquisition Device ◽  
Force Myography ◽  
Machine Interface ◽  
Insight Into

Force myography (FMG) is an emerging method to register muscle activity of a limb using force sensors for human–machine interface and movement monitoring applications. Despite its newly gained popularity among researchers, many of its fundamental characteristics remain to be investigated. The aim of this study is to identify the minimum sampling frequency needed for recording upper-limb FMG signals without sacrificing signal integrity. Twelve healthy volunteers participated in an experiment in which they were instructed to perform rapid hand actions with FMG signals being recorded from the wrist and the bulk region of the forearm. The FMG signals were sampled at 1 kHz with a 16-bit resolution data acquisition device. We downsampled the signals with frequencies ranging from 1 Hz to 500 Hz to examine the discrepancies between the original signals and the downsampled ones. Based on the results, we suggest that FMG signals from the forearm and wrist should be collected with minimum sampling frequencies of 54 Hz and 58 Hz for deciphering isometric actions, and 70 Hz and 84 Hz for deciphering dynamic actions. This fundamental work provides insight into minimum requirements for sampling FMG signals such that the data content of such signals is not compromised.

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