Ben Kröse
Biographic Data
| ID | 5120110 |
|---|---|
| NAME | Ben Kröse |
| GIVEN NAMES | Ben |
| FAMILY NAME | Kröse |
| SIGNATURE | BEN KRÖSE |
| AFFILIATIONS | Amsterdam University of Applied Sciences |
| ORCID | 0000-0003-1237-0618 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 0 |
What Are Good Situations for Running? A Machine Learning Study Using Mobile and Geographical Data
Running is a popular form of physical activity. Personal, social, and environmental determinants influence the engagement of the individual. To get insight in the relation between running behavior and external situations for different types of users, we carried out an extensive data mining study on large-scale datasets. We combined 4 years of historical running data (collected by a mobile exercise application from over 10K participants) with weat…
The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining
Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for de…
Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application
Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the 'right' time to deli…
Promoting Factors for Physical Activity in Children with Asthma Explored through Concept Mapping
For children with asthma, physical activity (PA) can decrease the impact of their asthma. Thus far, effective PA promoting interventions for this group are lacking. To develop an intervention, the current study aimed to identify perspectives on physical activity of children with asthma, their parents, and healthcare providers. Children with asthma between 8 and 12 years old ( n = 25), their parents ( n = 17), and healthcare providers ( n = 21) pa…
Assessing Acceptance of Assistive Social Agent Technology by Older Adults
This paper proposes a model of technology acceptance that is specifically developed to test the acceptance of assistive social agents by elderly users. The research in this paper develops and tests an adaptation and theoretical extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) by explaining intent to use not only in terms of variables related to functional evaluation like perceived usefulness and perceived ease of use, b…
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Assessing Acceptance of Assistive Social Agent Technology by Older Adults
This paper proposes a model of technology acceptance that is specifically developed to test the acceptance of assistive social agents by elderly users. The research in this paper develops and tests an adaptation and theoretical extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) by explaining intent to use not only in terms of variables related to functional evaluation like perceived usefulness and perceived ease of use, b…
Promoting Factors for Physical Activity in Children with Asthma Explored through Concept Mapping
For children with asthma, physical activity (PA) can decrease the impact of their asthma. Thus far, effective PA promoting interventions for this group are lacking. To develop an intervention, the current study aimed to identify perspectives on physical activity of children with asthma, their parents, and healthcare providers. Children with asthma between 8 and 12 years old ( n = 25), their parents ( n = 17), and healthcare providers ( n = 21) pa…
What Are Good Situations for Running? A Machine Learning Study Using Mobile and Geographical Data
Running is a popular form of physical activity. Personal, social, and environmental determinants influence the engagement of the individual. To get insight in the relation between running behavior and external situations for different types of users, we carried out an extensive data mining study on large-scale datasets. We combined 4 years of historical running data (collected by a mobile exercise application from over 10K participants) with weat…
The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining
Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for de…
Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application
Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the 'right' time to deli…
Computer Science (5 works) · Psychology (5 works) · Human–computer interaction (3 works) · Physical Activity and Health (3 works) · Applied Psychology (2 works) · Artificial Intelligence (2 works) · Digital Mental Health Interventions (2 works) · Intervention (counseling (2 works) · Mobile Health and mHealth Applications (2 works) · Social Psychology (2 works)