Visitsattapongse, Sarinporn

Loading...
Thumbnail Image
Preferred name
Visitsattapongse, Sarinporn
Alternative Name
Visitsattapongse, S.
Main Affiliation
Email
sarinporn.vi@kmitl.ac.th

Settings

Now showing 1 - 4 of 4
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Smart wheelchair based on eye tracking
    (2017-02-21)
    Wanluk, Nutthanan
    ;
    Visitsattapongse, Sarinporn
    ;
    Juhong, Aniwat
    ;
    Pintavirooj, C.
    This project is a smart wheelchair based on eye tracking which is designed for people with locomotor disabilities. The add-on controlled module can be used with any electrical wheelchair. The smart wheel chair consists of four modules including imaging processing module, wheelchair-controlled module, SMS manager module and appliance-controlled module. The image processing module comprises of a webcam installed on the eyeglass and C++ customized image processing software. The captured image which is transmitted to raspberry Pi microcontroller will be processed using OpenCV to derive the 2D direction of eye ball. The coordinate of eyeball movement is then wirelessly transmitted to wheelchair-controlled module to control the movement of wheel chair. The wheelchair-controlled module is two dimensional rotating stages that installed to the joystick of the electrical wheelchair to replace the manual control of the wheelchair. The motion of eyeball is also used as the cursor control on the raspberry Pi screen to control the operation of some equipped appliance and send message to smart phone.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Prototype Modeling of Bed for Bedridden Patients
    (2019-01-10)
    Bunkum, Manao
    ;
    Reanaree, Parkbhum
    ;
    Wanluk, Nutthanan
    ;
    Visitsattapongse, Sarinporn
    One of the most common health risks for bedridden patient is a pressure sore or decubitus ulcers. Pressure sore developed in people who are not able to move or lying in the same position for a long period of time. To solve this problem, a caregiver must change the patient's position every two hours if possible. In addition, the caregiver already has many kinds of care work to assist the patient such as changing clothes, administering medicine, daily health checking etc. This paper presented a design model of the bed used for bedridden patients, including paralysis, individuals with impaired mobility, and the elderly. The bed consists of an automatic bed lift control system and a patient monitoring system. The bed can change the patient's position in left or right tilt by lifting the left or right side of the bed up automatically. The system came with a graphic user interface to communicate with the caregiver or physician. The patient monitoring system including, the heart rate monitor, the body temperature monitor and the blood pressure monitor which are then sent to a home or hospital server. All data can then be remotely monitored by caretaker or physician. The proposed of the bed is designed to better assist the daily life of bedridden patients and caregivers.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Prototype of Wearable Device for Blood Pressure using Pulse Transit Time
    (2021-01-01)
    Bunkum, Manao
    ;
    Wanluk, Nutthanan
    ;
    Visitsattapongse, Sarinporn
    At present, there is a continuous increase in the number of patients suffering from hypertension in Thailand. and resulted in higher mortality rates as well. with an increasing trend every year Some people with high blood pressure need medication and regular monitoring of their blood pressure to prevent further complications. Most of these are pressure gauges that require a cuff that is wrapped around a patient's upper arm, wrist, or thigh. which is not convenient to carry for patients who need to measure blood pressure regularly This research proposes a prototype of a wearable device for measuring blood pressure using Pulse Transit Time (PTT) by measuring the pulse between the wrist and the index finger of the other hand. and take the pulse movement time to calculate the blood pressure Based on the results of testing prototypes of wearable devices for measuring pressure compared to commercially available pressure gauges. Of the five participants, the prototype of a wearable device for measuring pressure was approximately 94% accurate compared to commercially available pressure gauges. The prototype device can measure blood pressure in real time and is always portable.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Detection and Classification of COVID-19 Chest X-rays by the Deep Learning Technique
    (2022-01-01)
    Sonarra, Wannika
    ;
    Vongmanee, Naphatsawan
    ;
    Wanluk, Nutthanan
    ;
    Pintavirooj, Chuchat
    ;
    Visitsattapongse, Sarinporn
    The Coronavirus disease (COVID-19) infection has become a pandemic, and this is the most critical problem that has occurred in Thailand and also expanded all over the world. As such, it is not astonishing to know that this virus has had a direct effect on hospitals with the delayed screening of patients because of the increasing number of daily cases and the shortage of medical personnel and restricted treatment space. Due to such restrictions, in this study, we used a clinical decision-making system with predictive algorithms. Predictive algorithms could potentially ease the strain on healthcare systems by identifying the diseases. Moreover, image classification is one interesting aspect of image processing. Convolutional neural network (CNN) is a widely used algorithm for image classification by separating the images of the COVID-19 disease, images with a lung infection, and normal images. To evaluate the predictive performance of our models, precision, F1-score, recall, receiver operating characteristic (ROC) curve (area under the ROC curve), and accuracy scores were used. It was observed that the predictive models trained on the laboratory findings could be used to predict the COVID-19 infection as well and could be helpful for medical experts to appropriately prioritize the resources. This could be employed to assist medical experts in validating their initial laboratory findings and could also be used for clinical prediction studies.