Tangwongcharoen, Wisan

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Tangwongcharoen, Wisan
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Email
wisan.ta@kmitl.ac.th

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    Define Stance and Swing pattern of gait cycle using motion sensor and K-Mean Clustering
    (2022-01-01)
    Santikan, Piyapon
    ;
    Tangwongcharoen, Wisan
    ;
    Kimpan, Warangkhana
    This research studied walking patterns based on the gait cycle focused on the stance and swing period. We are interested in creating the pattern for representing a normal person and person with a walking disorder by distinguishing patterns. This research uses Razor-IMU to collect all walking data and transfer data from sensors via WIFI which helps gain data to be stable and accurate.After collecting the walking data, we transformed data into linear graphs to reference the gait cycle pattern. Because the graph in linear form can show the movement and distinguish between normal and abnormal people the difference. The aim is to obtain representative data of normal and abnormal people for further analysis. Therefore, the data were then grouped using K-mean Clustering. The data obtained from the clusters were able to distinguish between normal and abnormal walking distances.
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    A Development of Knee Support for Vastus Medialis Oblique Muscles for Thai Patients
    (2020-06-01)
    Saklertwilai, Sira
    ;
    Tangwongcharoen, Wisan
    ;
    Churdchomjan, Worachart
    This study proposed the design of knee training and equipment for the Thai people physiology. This equipment allows the patient to fully control the stretching of the knee, the Vastus Medialis Oblique (VMO) movement fully extended. The researchers developed a knee support training device using an IMU sensor attach to the knee and sent knee extension exercise data to the tablet via Wi-Fi. The training program support 3 postures; sit and move the leg forward, stand up and move the leg backward, stand up and move the leg beside. Training provides 4 games to simulate a knee extension. Trainees control knee movement to control the direction of the game. The experimental result was gaining from 70 participants who are aging 18-45 all genders, with VMO weakness, Testers was divided into 2 groups: did only exercise, exercise using Trigo wireless. Electromyography (EMG) is a measure of the level of knee stretching at the end of the movement of VMO and Vastus Lateralis (VL), which used in exercise for the treatment of knee pain. The evaluation based on the patient's stretching ability and the practice. The results of tester who using the training tools have improvement. The ability to flex the knee can be increasing by an average of 36° (in the range 0° - 90°) and the average pain level was decreasing by 3.1 levels (in the range of 0 - 10 levels). From the experimental results, the development of training as a model for the development of a knee support training program prevented injury in the elderly and muscle recovery from deterioration and injury.
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    Walking pattern analysis using the gait cycle to classify a healthy and an unhealthy form
    (2023-01-01)
    Suntikan, Piyapon
    ;
    Tangwongcharoen, Wisan
    This study proposed an algorithm to classify normal and abnormal forms of walking patterns by identifying the swing and stance phases, known as the gait cycle. The walking patterns were examined by collecting data using Razor IMU sensors. The Wi-Fi transmitter was utilized to transfer raw data for further analysis, representing the gait cycle using a linear graph. The data were preprocessed and transformed into phase graphs using the polar coordinate equation. To identify areas of density, data were incorporated into K-mean clustering. A k-value of 2 groups represented the major walking phases and classified patterns based on a regional model. The experimental results enable us to define healthy and unhealthy forms. This algorithm conveniently assists in diagnosing basic physical conditions, and the dataset is efficient for monitoring the medical treatment process among recipients.