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Optical-based foot plantar pressure measurement system for potential application in human postural control measurement and person identification
(2021-07-01)
Keatsamarn, Tanapon
;
Visitsattapongse, Sarinporn
;
Aoyama, Hisayuki
;
Pintavirooj, Chuchart
Plantar pressure, the pressure exerted between the sole and the supporting surface, has great potentialities in various research fields, including footwear design, biometrics, gait analysis and the assessment of patients with diabetes. This research designs an optical-based foot plantar pressure measurement system aimed for human postural control and person identification. The proposed system consists of digital cameras installed underneath an acrylic plate covered by glossy white paper and mounted with LED strips along the side of the plate. When the light is emitted from the LED stripes, it deflects the digital cameras due to the pressure exerted between the glossy white paper and the acrylic plate. In this way, the cameras generate color-coded plantar pressure images of the subject standing on the acrylic-top platform. Our proposed system performs personal identification and postural control by extracting static and dynamic features from the generated plantar pressure images. Plantar pressure images were collected from 90 individuals (40 males, 50 females) to develop and evaluate the proposed system. In posture balance evaluation, we propose the use of a posture balance index that contains both magnitude and directional information about human posture balance control. For person identification, the experimental results show that our proposed system can achieve promising results, showing an area under the receiver operating characteristic (ROC) curve of 0.98515 (98.515%), an equal error rate (EER) of 5.8687%, and efficiency of 98.515%.
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Multi-parameter vital sign telemedicine system using web socket for covid-19 pandemics
(2021-03-01)
Pintavirooj, Chuchart
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Keatsamarn, Tanapon
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Treebupachatsakul, Treesukon
Telemedicine has become an increasingly important part of the modern healthcare infras-tructure, especially in the present situation with the COVID-19 pandemics. Many cloud platforms have been used intensively for Telemedicine. The most popular ones include PubNub, Amazon Web Service, Google Cloud Platform and Microsoft Azure. One of the crucial challenges of telemedicine is the real-time application monitoring for the vital sign. The commercial platform is, by far, not suitable for real-time applications. The alternative is to design a web-based application exploiting Web Socket. This research paper concerns the real-time six-parameter vital-sign monitoring using a web-based application. The six vital-sign parameters are electrocardiogram, temperature, plethysmogram, percent saturation oxygen, blood pressure and heart rate. The six vital-sign parameters were encoded in a web server site and sent to a client site upon logging on. The encoded parameters were then decoded into six vital sign signals. Our proposed multi-parameter vital-sign telemedicine system using Web Socket has successfully remotely monitored the six-parameter vital signs on 4G mobile network with a latency of less than 5 milliseconds.
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Optical-based foot plantar pressure measurement with application in human postural balance, gait and recognition analysis
(2020-07-01)
Keatsamarn, Tanapon
;
Visitsattapongse, Sarinporn
;
Pintavirooj, Chuchart
;
Aoyama, Hisayuki
In this research, we purposed the design of real-time low-cost marker-free optical-based plantar-pressure measurement with application in human postural control, gait and recognition analysis. The system consists of a series of digital cameras capture installed underneath the acrylic-top platform. Light of LED strip mounted along the side of the acrylic plate deflected by the pressure exerted between the glossy white paper installed in the top of acrylic and the acrylic plate to the digital cameras provides the color-coded plantar pressure image of the subject standing on the platform. The system can provide both static features and dynamic features. Our hybrid system consists of a series of USB cameras aligned under the acrylic-plate walking platform. The mosaic image processing is used to concatenate the captured image to increase the sensing area. Captured the image data in video mode, various dynamic parameters can be derived for further dynamic analysis. The image capturing in one specific frame can be used for static analysis. Application in human-postural measurement, gait analysis, and person identification indicate that our system is an all-in-one system for plantar pressure measurement.
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Footprint Identification using Deep Learning
(2019-01-10)
Keatsamarn, Tanapon
;
Pintavirooj, Chuchart
Human footprint is the biometric system of the individual person. Everyone has specific footprints. It can be used instead of password-based authentication in the security system such as a user authentication for the financial transaction. The password-based system cannot verify that the person who entered the password is valid or not. Therefore the biometric system is more secure than the password-based system. For that reason, it's interesting to use footprint image in the creating of the footprint-based identification system. In this paper, the convolutional neural network training is used for deep learning classification. Convolutional neural networks are essential for deep learning and suited for image recognition.
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Embedded foot plantar classification system using Raspberry Pi
(2018-05-30)
Niemhom, Anyamanee
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Keatsamarn, Tanapon
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Pintavirooj, Chuchart
Foot plantar classification is crucial to prevent dangers to patient's health that originated from an abnormal type of foot. When patients comprehend their type of foot, they will be able to form personal insole to prevent a hazard. On the contrary, some patients who ignore their risk will possibly have the problem. We design the system to classify type of foot by measuring foot pressure and foot curvature. For the software, we use webcams to capture the foot images that will be further processed by Raspberry Pi with OpenCV and color coding which correspond to foot pressure. For the hardware system, we use the component which is inexpensive and easily available. The hardware structure is composed of steel as a base where the transparent acrylic plate and glossy white paper is placed on. The black polypropylene sheet covering on the uppermost is used to block light from outside. Aligned on the side of the transparent acrylic plate LED strip is used for light source for the system. Underneath the steel base there are four webcams which is used to record feet images (two webcams for each foot). The images are sent to Raspberry Pi for image processing and displaying. The system is able to classify three types of the foot for patients including normal foot, high arch foot, and flat foot.
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Foot plantar pressure measurement system using optical sensor
(2017-02-21)
Keatsamarn, Tanapon
;
Pintavirooj, Chuchart
Foot pressure measurement is necessary for classifying disorders of the foot and designing insole for individual person. This present work uses optical sensor (webcam) to capture the foot-pressure image. Image processing on Raspberry Pi with OpenCV library is applied to process image and color coding corresponding to foot pressure. The hardware system uses the transparent acrylic plate and uses the steel as a base of the acrylic plate. The glossy white paper is placed on the top of the transparent acrylic plate covering with polypropylene sheet on the system to block light from outside. Light in the system is released from LED strip entering from a side of the acrylic plate. The scattered light occurred in acrylic plate from the foot pressing were recorded by the webcams. The four webcams placed below facing upward for collecting images (2 cameras for each foot) and sending to Raspberry Pi. Raspberry Pi will perform image process including image enhancement and image stitching and image displaying. The result can be used to classifying foot type and find methods to prevent the occurrence of for disorders.

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