Exending Students’ Skills and Knowledge to Designing and Implementing Personal Fitness Plans

Keyword(s):  
Author(s):  
Carolin Siepmann ◽  
Pascal Kowalczuk

AbstractSmartwatches are the most popular wearable device and increasingly subject to empirical research. In recent years, the focus has shifted from revealing determinants of smartwatch adoption to understanding factors that cause long-term usage. Despite their importance for personal fitness, health monitoring, and for achieving health and fitness goals, extant research on the continuous use intention of smartwatches mostly disregards health and fitness factors. Grounding on self-determination theory, this study addresses this gap and investigates the impact of health and fitness as well as positive and negative emotional factors encouraging or impeding consumers to continuously use smartwatches. We build upon the expectation-confirmation model (ECM) and extend it with emotional (device annoyance and enjoyment) as well as health and fitness factors (goal pursuit motivation and self-quantification behavior). We use structural equation modeling to validate our model based on 335 responses from actual smartwatch users. Results prove the applicability of the ECM to the smartwatch context and highlight the importance of self-quantification as a focal construct for explaining goal pursuit motivation, perceived usefulness, confirmation and device annoyance. Further, we identify device annoyance as an important barrier to continuous smartwatch use. Based on our results, we finally derive implications for researchers and practitioners alike.


2018 ◽  
Vol 23 (7) ◽  
pp. 1020-1037 ◽  
Author(s):  
Michael Zimmer ◽  
Priya Kumar ◽  
Jessica Vitak ◽  
Yuting Liao ◽  
Katie Chamberlain Kritikos
Keyword(s):  

Author(s):  
Parian Haghighat ◽  
Aden Prince ◽  
Heejin Jeong

The growth in self-fitness mobile applications has encouraged people to turn to personal fitness, which entails integrating self-tracking applications with exercise motion data to reduce fatigue and mitigate the risk of injury. The advancements in computer vision and motion capture technologies hold great promise to improve exercise classification performance. This study investigates a supervised deep learning model performance, Graph Convolutional Network (GCN) to classify three workouts using the Azure Kinect device’s motion data. The model defines the skeleton as a graph and combines GCN layers, a readout layer, and multi-layer perceptrons to build an end-to-end framework for graph classification. The model achieves an accuracy of 95.86% in classifying 19,442 frames. The current model exchanges feature information between each joint and its 1-nearest neighbor, which impact fades in graph-level classification. Therefore, a future study on improved feature utilization can enhance the model performance in classifying inter-user exercise variation.


2019 ◽  
Vol 61 (11) ◽  
pp. e445-e451
Author(s):  
Ryutaro Matsugaki ◽  
Mika Sakata ◽  
Hideaki Itoh ◽  
Yasuyuki Matsushima ◽  
Satoru Saeki

2010 ◽  
Vol 38 (7) ◽  
pp. 895-905 ◽  
Author(s):  
Wen-Yu Chiu ◽  
Yuan-Duen Lee ◽  
Tsai-Yuan Lin

Not only are personal trainers the face of the personal fitness industry, they also generate a significant portion of revenue in this multi-billion dollar business. It is therefore essential to produce the best possible personnel. In order to assist the industry in selecting the best trainers, we developed a preliminary personal trainer evaluation system based on a survey of experts. The analytic hierarchy process (AHP) method was then applied to the system. Of the three major dimensions – achievement, teaching, and service results – achievement results, which include course sales and team achievement, were identified as the most important.


1882 ◽  
Vol 27 (120) ◽  
pp. 483-503
Author(s):  
C. Lockhart Robertson

Gentlemen,—In now opening the eighth section of this great International Medical Congress, and in offering to the alienists of Europe and America our cordial welcome to London, I must ask leave to explain to you that it is only by the accident of official position as senior physician to the Lord Chancellor, who, under the Royal prerogative and by statute, has in England the guardianship of all lunatics and persons of unsound mind, that I occupy to-day this presidential chair. But for the desire of the Executive Committee thus to recognise the paramount authority of the Lord Chancellor in our department of medicine, I cannot doubt that the place I now fill would have been allotted to our most distinguished English writer on lunacy, Dr. J. C. Bucknill, one of the vice-presidents of this Congress, whose writings and whose name are a household word in all the asylums where the English tongue is spoken. Called from my official position rather than from personal fitness to preside in this section, I may the more venture to ask at your hands a generous interpretation of my efforts, so to guide your deliberations here that they may advance the science and practice of this department of medicine in which we are all enrolled.


2017 ◽  
Vol 49 (5S) ◽  
pp. 444-445
Author(s):  
Tinker D. Murray ◽  
Gene Power ◽  
Lisa Roslanova ◽  
James Eldridge

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