TY - GEN
T1 - Calorie Burn Estimator on Stationary Bike using Human Body Pose Detector
AU - Batan, Iwap Saputra
AU - Yuniarno, Eko Mulyanto
AU - Purnomo, Mauridhi Hery
AU - Ramadhani, Ahmad
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - During the pandemic, we must maintain our body's immunity at best. Outdoor activities have been closed; therefore, there are limitations to activities that can be done. A solution to staying healthy during the pandemic is indoor exercise. One type of indoor exercise is regularly riding stationary bikes. We maintain the body's fitness and burn calories by riding stationary bikes. However, some stationary bikes could not show accurate calories burned; they calculated it only based on speed, resistance, and duration, so people with different weights seem to burn the same amount of calories. Therefore, this paper proposed an additional parameter essential in calorie burning: body weight. We used the human body pose estimator to detect the activity of riding the stationary bike and calculated it by adding the person's weight. The result shows a difference between the estimated calorie burned and the data directly from the stationary bike. The difference is between 0.0225 to 2.8775. The heavier the person, the more differences in the calories burned. The proposed method helped prove that a person's weight affects the calories burned while doing an activity, especially riding a stationary bike.
AB - During the pandemic, we must maintain our body's immunity at best. Outdoor activities have been closed; therefore, there are limitations to activities that can be done. A solution to staying healthy during the pandemic is indoor exercise. One type of indoor exercise is regularly riding stationary bikes. We maintain the body's fitness and burn calories by riding stationary bikes. However, some stationary bikes could not show accurate calories burned; they calculated it only based on speed, resistance, and duration, so people with different weights seem to burn the same amount of calories. Therefore, this paper proposed an additional parameter essential in calorie burning: body weight. We used the human body pose estimator to detect the activity of riding the stationary bike and calculated it by adding the person's weight. The result shows a difference between the estimated calorie burned and the data directly from the stationary bike. The difference is between 0.0225 to 2.8775. The heavier the person, the more differences in the calories burned. The proposed method helped prove that a person's weight affects the calories burned while doing an activity, especially riding a stationary bike.
KW - calorie burn estimator
KW - human body pose
KW - stationary bike
UR - http://www.scopus.com/inward/record.url?scp=85171139659&partnerID=8YFLogxK
U2 - 10.1109/ISITIA59021.2023.10221128
DO - 10.1109/ISITIA59021.2023.10221128
M3 - Conference contribution
AN - SCOPUS:85171139659
T3 - 2023 International Seminar on Intelligent Technology and Its Applications: Leveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding
SP - 125
EP - 129
BT - 2023 International Seminar on Intelligent Technology and Its Applications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023
Y2 - 26 July 2023 through 27 July 2023
ER -