Identifying and Evaluating User Requirements for Smartphone Group Fitness Applications

Luhanga, Edith Talina; Hippocrate, Akpa Akpro Elder; Suwa, Hirohiko; Arakawa, Yutaka; Yasumoto, Keiichi

doi:10.1109/access.2018.2793844

Cited by 23 publications

(18 citation statements)

References 34 publications

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“…The two other participants reported exercise once or twice a week when they have time but not on a regular basis. Three participants were also participants of our previous study about users' requirements for a smartphone fitness application, and they were highly motivated to see how our smart glove could help them to improve their workout performance [29].…”

Section: Methodsmentioning

confidence: 99%

A Smart Glove to Track Fitness Exercises by Reading Hand Palm

et al. 2019

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Medical studies have intensively demonstrated that sports activity can enhance both the mental and the physical health of practitioners. In recent years, fitness activity became the most common way to motivate and engage people in sports activity. Recently, there have been multiple attempts to elaborate on the “ideal” IoT-based solution to track and assess these fitness activities. Most fitness activities (except aerobic activities like running) involve one or multiple interactions between the athlete’s hand palms and body or between the hand palms and the workout materials. In this work, we present our idea to exploit these biomechanical interactions of the hand palms to track fitness activities via a smart glove. Our smart glove-based system integrates force-sensitive resistor (FSR) sensors into wearable fitness gloves to identify and count fitness activity, by analyzing the time series of the pressure distribution in the hand palms observed during fitness sessions. To assess the performance of our proposed system, we conducted an experimental study with 10 participants over 10 common fitness activities. For the user-dependent activity recognition case, the experimental results showed 88.90% of the F score for overall activity recognition. The result of leave-one-participant-out cross-validation showed an F score ranging from 58.30% to 100%, with an average of 82.00%. For the exercise repetition count, the system achieved an average counting error of 9.85%, with a standard deviation of 1.38.

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Section: Methodsmentioning

confidence: 99%

A Smart Glove to Track Fitness Exercises by Reading Hand Palm

et al. 2019

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“…We also considered incorporation of gamification techniques [10], [11], [55], [56] into the workplace. For example, gamification and sensing techniques can be used to solve reservation problems in offices.…”

Section: Changing Workplace Behavior With Nudgesmentioning

confidence: 99%

Sensing and Changing Human Behavior for Workplace Wellness

Arakawa

2019

Journal of Information Processing

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Recently, companies have begun to care more about the well-being of their employees. With the spread of sensors, the Internet of Things, and artificial intelligence, the movement to build a better working environment by utilizing these technologies has been spreading. Especially, research on behavior that can change lifestyle habits is becoming popular. In this paper, we summarize workplace behavior research and projects for sensing and changing human behavior in a workplace and aim to improve the productivity and wellness of employees. Also, we introduce concepts for future workplaces and some of our related achievements. For physical state sensing, we have developed a continuous posture-sensing chair, which will soon be available commercially. For internal state sensing, we propose a method for estimating quality of life with wearable sensors. Our system have already achieved to estimate QoL (Quality of Life) around 90% with only 9 questions. In addition, we propose interactive digital signage to provide habit-changing reminders. Through one month experiment, we confirmed that our system can be feasible in daily life.

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“…Some examples of BCSSs using social support include Jaques et al who developed a web-based pairing application in which the two paired participants need to help each other with achieving their goals like drinking more water [10]. Luhanga et al conducted a study in which they sought to promote behavior change in losing weight and balanced diet by using social competition among group members [11].…”

Section: A Examples Of Bcssmentioning

confidence: 99%

“…However, it may also harm users' motivation if the system doesn't cover privacy and social relationship. Luhanga et al 's system shared all the information including the failed tasks that users did which might affect the privacy and social relationship and increase the unwillingness of using the system [11]. Therefore, the privacy problem should be carefully considered when we apply social support to our design.…”

Section: B Strategies Used In Current Systems and Their Weaknessesmentioning

confidence: 99%

Design of Behavior Change Environment with Interactive Signage Having Active Talk Function

Zhang

Arakawa²,

Oinas-Kukkonen

2019

2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)

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In this paper, we construct an interactive signage system, which is able to actively talk to users who are passing the signage system and at the same time tries to induce behavioral changes through visual and auditory stimulation. On top of our previous feasibility study, we re-design our proposed system based on the persuasive system design (PSD) model and the behavior change support system (BCSS) theory. The new design consists of 4 parts: recognizing (identifying and classifying users), executing (sending triggers and inducing behavior change), reviewing (recording users' reaction), and feedback (keeping or improving users' motivation). To track users' status and performance, we use the smartphone and the smartwatch to collect users' bio-data (e.g. heart rate, number of steps) and users' location. To send user triggers continuously without being interrupted by notifications from other applications, we set the interactive signage in the daily action line of users and present information to users when they pass the signage. In order to make the system more persuasive, we pick up eight features from the 28-feature list of PSD and apply them to our design.Index Terms-behavior change, interactive signage, beacon, environment side, behavior change support system, persuasive system design

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Identifying and Evaluating User Requirements for Smartphone Group Fitness Applications

Cited by 23 publications

References 34 publications

A Smart Glove to Track Fitness Exercises by Reading Hand Palm

A Smart Glove to Track Fitness Exercises by Reading Hand Palm

Sensing and Changing Human Behavior for Workplace Wellness

Design of Behavior Change Environment with Interactive Signage Having Active Talk Function

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