Discussing Risks and Benefits in the Future of Hybrid Rehabilitation and Fitness in Mixed Reality
May 16, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jana Franceska Funke, Enrico Rukzio
arXiv ID
2405.10059
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
In a world where in-person context transitions more into remote and hybrid concepts, we should consider new concepts of interaction in health and rehabilitation and what advantages and disadvantages they bring. One of the rising topics is mixed reality, where we can use the advantages of immersive 3D, 360-degree environments. Meanwhile, physical activity is further decreasing and with it negative effects increase through sedentary behaviour or wrong and untrained movements. In this position paper, we discuss these new risks and potential benefits of mixed reality technology when used for rehabilitation and fitness. We conclude with suggesting better feedback and guidance for physical movement and tasks at home. Improving feedback and guidance for participants could be achieved through using new technologies like virtual reality and motion tracking.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted