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Your search keyword '"Elder Akpro Hippocrate Akpa"' showing total 2 results
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2 results on '"Elder Akpro Hippocrate Akpa"'

1. Smartphone-Based Food Weight and Calorie Estimation Method for Effective Food Journaling

Author

Elder Akpro Hippocrate Akpa, Hirohiko Suwa, Yutaka Arakawa, and Keiichi Yasumoto

Subjects
calorie estimation, food weight measurement, eating tools, image processing, food journal, Control engineering systems. Automatic machinery (General), TJ212-225
Abstract

World health statistics about overweight and obesity show that overweight, obesity and diet-related diseases still remain major health risks. According to the World Health Organization, most of the world's population live in countries where overweight and obesity kill more people than underweight. Recently, many studies have been driven by the motivation of elaborating the “ideal” solutions to prevent and/or monitor overweight, obesity and diet-related diseases, and to encourage healthy diet and lifestyle. In this work, we present our idea to automatically measure food weight and calories, from food photo using ordinary chopsticks as a measurement reference. The analysis of the obtained results show that the use of near-by eating utensils combined with computer vision techniques is a great and exploitable approach to ubiquitously help in diet assessment and obesity treatment.

Published
2017
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2. GIFT: Glove for Indoor Fitness Tracking System

Author

Hirohiko Suwa, Keiichi Yasumoto, Masashi Fujiwara, Elder Akpro Hippocrate Akpa, and Yutaka Arakawa

Subjects
Activity tracking, biology, business.industry, Computer science, Athletes, Physical health, Tracking system, 02 engineering and technology, biology.organism_classification, Coaching, Multiple sensors, Activity recognition, 03 medical and health sciences, 0302 clinical medicine, Force-sensing resistor, Human–computer interaction, 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, 030212 general & internal medicine, business
Abstract

It has been intensively demonstrated that physical activity can enhance the mental and physical health of practitioners. In recent years, fitness activities became the most common way to engage in physical activities. In this paper, we propose a smart-glove based fitness activity tracking system that can detect athletes activities in any indoor fitness facility, with no need of attaching multiple sensors on the athlete’s body. The system adopts force sensitive resistor (FSR) sensors to identify the type of exercise by analyzing the pressure distribution in the hand palm during fitness activities. To evaluate the performance of our proposed system, we ran a pilot study with 10 healthy participants over 10 common fitness activities. The experimental results showed an overall recognition accuracy rate of 87%. We believe the promising results would contribute to the works on personal assisted coaching systems and create enjoyable experiences when performing fitness activities.

Published
2018
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