TY - JOUR
T1 - Monitoring System with Cross-Type Capacitive Plantar Pressure Sensor
AU - Tsai, Tzung Min
AU - Tsou, Chieh
AU - Huang, Peng Wei
AU - Lee, Shuenn Yuh
AU - Chang, Soon Jyh
N1 - Funding Information:
Manuscript received February 22, 2020; revised April 10, 2020 and May 3, 2020; accepted May 13, 2020. Date of publication May 19, 2020; date of current version September 3, 2020. This work was supported in part by the Taiwan Semiconductor Research Institute and the Ministry of Science and Technology (MOST), Taiwan, under Grant MOST 108-2218-E-006-020 and Grant MOST 109-2622-8-006-021-TE2. The associate editor coordinating the review of this article and approving it for publication was Prof. Tien-Kan Chung.(Corresponding author: Shuenn-Yuh Lee.) The authors are with the Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan (e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]). Digital Object Identifier 10.1109/JSEN.2020.2995715
Publisher Copyright:
© 2001-2012 IEEE.
PY - 2020/10/1
Y1 - 2020/10/1
N2 - This study presents a monitoring system with a 4 ×4 handmade cross-type capacitive plantar pressure (CCPP) sensor. This system includes a prototype detection module and a display interface, and it is implemented as a wearable device. The prototype detection module consists of a low dropout regulator (commercial IC) utilized to regulate a stable DC voltage with 3.7 V Li-ion battery for a whole wearable device and a customized capacitance-to-digital converter (CDC) chip is employed to convert capacitances into the digital data. The CDC includes a capacitance-to-voltage converter (CVC) and 10-bit successive approximation register analog-to-digital converter are fabricated via the TSMC 0.18 μ m 1P6M 3.3 V process. CVC is characterized by its selectability of detection points from 1 to 64 (8×8 cross-type capacitive array). This type of converter is controlled by digital codes of a field-programmable gate array (FPGA) and has embedded functions of a self-separated input signal, which is applied to scan each detection point of the cross-type capacitive sensors, and a crosstalk attenuation (CA) is used to reduce parasitic capacitances and the effects of relative humidity and temperature of the environment for cross-type capacitive sensors. To demonstrate improvements of the CA, a multi-physics simulation software, COMSOL Multiphysics, was utilized to verify the performance of the CA. The handmade 4 ×4 CCPP sensor is modeled in COMSOL Multiphysics and simulated with/without CA. Finally, the simulated results reveal that the function of CA can reduce parasitic capacitances and the effects of the relative humidity and temperature caused by the environment effectively at the femtofarad level. The cross-type structure of a capacitive array has an advantage due to an Mtimes; N array, which only requires M + N tracks of input/output (I/O) ports to reduce the complexity of I/O connections. The measured results of the prototype detection module shown on the display interfaces reveal the positions and strengths of the corresponding capacitances of the CCPP sensor. The range of sensing capacitance is from 0 pF to 5.406 pF, the minimum sensing step is 15 fF, the accuracies of the handmade CCPP sensor and prototype detection module are-11.6/9.96 % and-8.65/5.54 %, respectively, and the sensitivity is 8 fF/N. The conversion time for one capacitance is 0.28 ms, and the maximum conversion time for 64 capacitances is 18.29 ms.
AB - This study presents a monitoring system with a 4 ×4 handmade cross-type capacitive plantar pressure (CCPP) sensor. This system includes a prototype detection module and a display interface, and it is implemented as a wearable device. The prototype detection module consists of a low dropout regulator (commercial IC) utilized to regulate a stable DC voltage with 3.7 V Li-ion battery for a whole wearable device and a customized capacitance-to-digital converter (CDC) chip is employed to convert capacitances into the digital data. The CDC includes a capacitance-to-voltage converter (CVC) and 10-bit successive approximation register analog-to-digital converter are fabricated via the TSMC 0.18 μ m 1P6M 3.3 V process. CVC is characterized by its selectability of detection points from 1 to 64 (8×8 cross-type capacitive array). This type of converter is controlled by digital codes of a field-programmable gate array (FPGA) and has embedded functions of a self-separated input signal, which is applied to scan each detection point of the cross-type capacitive sensors, and a crosstalk attenuation (CA) is used to reduce parasitic capacitances and the effects of relative humidity and temperature of the environment for cross-type capacitive sensors. To demonstrate improvements of the CA, a multi-physics simulation software, COMSOL Multiphysics, was utilized to verify the performance of the CA. The handmade 4 ×4 CCPP sensor is modeled in COMSOL Multiphysics and simulated with/without CA. Finally, the simulated results reveal that the function of CA can reduce parasitic capacitances and the effects of the relative humidity and temperature caused by the environment effectively at the femtofarad level. The cross-type structure of a capacitive array has an advantage due to an Mtimes; N array, which only requires M + N tracks of input/output (I/O) ports to reduce the complexity of I/O connections. The measured results of the prototype detection module shown on the display interfaces reveal the positions and strengths of the corresponding capacitances of the CCPP sensor. The range of sensing capacitance is from 0 pF to 5.406 pF, the minimum sensing step is 15 fF, the accuracies of the handmade CCPP sensor and prototype detection module are-11.6/9.96 % and-8.65/5.54 %, respectively, and the sensitivity is 8 fF/N. The conversion time for one capacitance is 0.28 ms, and the maximum conversion time for 64 capacitances is 18.29 ms.
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U2 - 10.1109/JSEN.2020.2995715
DO - 10.1109/JSEN.2020.2995715
M3 - Article
AN - SCOPUS:85091018996
SN - 1530-437X
VL - 20
SP - 11138
EP - 11155
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 19
M1 - 9096334
ER -