Heart Rate Prediction for Easy Walking Route Planning

Shogo Maenaka, Hirohiko Suwa, Yutaka Arakawa, Keiichi Yasumoto

Research output: Contribution to journalArticlepeer-review


<p>In this paper, aiming to support easy walking route planning, we propose methods for predicting a heart rate along the arbitrary route without walking data, and recommending a semi-optimal walking route based on the predicted results. In our method, we build a model to predict the heart rate during walking with expected walking speed and gradient along a target route, and compute a semi-optimal walking route (near least physical load route satisfying calorie/distance constraints requested by a user) by using the model. In order to evaluate the accuracy of the prediction model, a walking experiment with 39 participants was conducted. The result showed that our model could predict the heart rate with mean absolute error (MAE) of 6.31 beats per minute on average. We also confirmed that the route recommended by our method satisfied calorie/distance constraints requested by a user while keeping the average and the maximum physical load (in terms of heart rate reserve) at 29.5% (light load) and 44.4% (moderate load), respectively.</p>
Original languageEnglish
Pages (from-to)284-291
Number of pages8
JournalSICE Journal of Control, Measurement, and System Integration
Issue number4
Publication statusPublished - 2018


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