PRE2024 3 Group9: Difference between revisions
No edit summary |
|||
| Line 35: | Line 35: | ||
== User requirements == | == User requirements == | ||
'''User requirements + articles''' | |||
1. '''Low-impact dance movements for elderly users''' | |||
Create dance programmes that include low-impact movements specifically designed for older users. Incorporate well-controlled ballet and tap dance movements that can be performed by the robot, focusing on arm, hand and head movements that the Pepper robot can demonstrate. With such an approach, older participants can perform the activities sitting or standing, improving their physical endurance, strength and functionality in a safe way. Movement that maintains flexibility and reduces pain does not increase the risk of injury, but has been shown to encourage very high levels of adherence among participants to demonstrate effectiveness and also something worth doing (Green et al., 2024). Including aspects of aerobics that reduce psychological stress and possible mood enhancement would be valuable, as indicated by a study in which low-impact aerobic dance exercises significantly improved stress levels among sedentary women in Malaysia (Johar et al., 2012). | |||
2. '''Mood enhancement''' | |||
'''Intermittent dance exercises''' | |||
The robot should have intermittent aerobic dance exercises of light intensity (I-LADE) as its core activity. This exercise is considered the best to improve mood in older adults because it is very fun and engaging. According to a study published in 2021 in Frontiers in Aging Neuroscience, both forms of exercise interventions (continuous and intermittent) had a positive impact on mood and executive functions. However, the I-LADE (intermittent) intervention was particularly beneficial because it was more fun, which made it most likely to increase participation for longer. Participants reported that this intervention was clearly more pleasurable and enjoyable than continuous physical activity, allowing this intervention to be included fairly regularly in treatment programmes for older adults, especially as a morale booster (Frontiers in Aging Neuroscience, 2021). | |||
'''Classical music''' | |||
The robot should include classical music with a happy sound, specifically pieces by Mozart, to help improve the mood and cognitive functioning of elderly users. Such music would use the general inherent characteristics of classical compositions to evoke happiness and would therefore be suitable dancing programs to boost mood. Research suggests that listening to happy-sounding music, such as Mozart's, can significantly increase the level of arousal and mood in older people. This kind of music is not only good for mood but also for cognitive functions, working memory and skills needed for voluntary mental activity in older people to maintain overall mental health (Vincenzi et al., 2022). | |||
'''Personalized music''' | |||
Personalised music interventions could include using favourite genres and songs to improve mood in older users, especially those with stroke or dementia. The robot will facilitate music sessions that are personalised to evoke positive emotional responses that improve mood. Teppo Särkämö's research proves that personalised music, especially well-known and favourite songs, plays a crucial role in improving the mood and emotional well-being of elderly people. Such interventions take advantage of the very close emotional relationships users have with music they like, and activate positive memories and feelings that are exceptionally strong for improving mood. It emphasizes that familiar music evokes stronger emotional responses and activates reward circuits in the brain more effectively than unfamiliar music. | |||
3. '''Customization of movement intensity to ensure safety and comfort for all users''' | |||
The system should be able to adjust movement intensity and style so that all users, particularly older users, feel safe and comfortable. Older users may have varying levels of physical ability. Balance and type of movements should be modified to ensure the safety and comfort of the programme for older participants. This modification is due to the fact older individuals do not have comparable physical capabilities, as inscribed in the synthesis evidence from recent studies on health programmes in dance. Such customized approaches minimize injury risk in dance activities while promoting greater overall participation by making movements accessible and enjoyable for all participants, irrespective of their physical condition. (Waugh et al., 2024). | |||
4. '''Hands-Free Controls''' | |||
The robot must feature hands-free controls, such as voice commands, so that users with mobility or cognitive limitations can still use the robot. According to Zhao et al (2023), human-robot interaction, perception-based systems and prediction-based systems design to adapt to the user's needs while ensuring safety and comfort. Dance therapy is usually defined as artistic therapy, i.e. coordinated movements and balanced use of music; hands-free control allows the user to interact with the robot without diverting their attention or requiring manual input. In addition, voice controls also enable interaction where users can start, stop or tune dance routines without the burden of physical control input that can be difficult for those with less dexterity or cognitive limitations. Another advantage is that voice guidance can provide real-time encouragement, corrections or instructions that can increase motivation and support dance sessions. Psychological safety has also been shown to greatly aid user acceptance of robotic systems (Zhao et al., 2023). Letting users control the robot with words rather than by moving their body reduces worry and increases confidence, especially among people who are not so used to technology. | |||
5. '''Clear visual and audio guidance''' | |||
Research on interactive robotic feedback and balance therapy demonstrates that customized movement intensity, real-time feedback, and hands-free controls significantly improve adherence, engagement, and motor functions in older people (Segal et al., 2022). | |||
'''Bibliography''' | |||
1. Kimberly Lazo Green, Yang Yang, Ukachukwu Abaraogu, Claire H Eastaugh, Fiona R Beyer, Gill Norman, Chris Todd, Effectiveness of dance interventions for falls prevention in older adults: systematic review and meta-analysis, ''Age and Ageing'', Volume 53, Issue 5, May 2024, afae104, <nowiki>https://doi.org/10.1093/ageing/afae104</nowiki> | |||
2. Johar, M., Omar-fauzee, M. S., Abu Samah, B., & Abd Rashid, S. (2012). Effect of low-impact aerobic dance exercise on psychological health (stress) among sedentary women in Malaysia. ''Biology of Sport, 29''(1). Effect_of_low-impact_aerobic_dance_exercise_on_psy.pdf | |||
3. Frontiers in Aging Neuroscience. (2021). ''Comparison between the effects of continuous and intermittent light-intensity aerobic dance exercise on mood and executive functions in older adults''. Retrieved from <nowiki>https://www.frontiersin.org/articles/10.3389/fnagi.2021.723243/full</nowiki> | |||
4. Vincenzi, M., Borella, E., Sella, E., Lima, C. F., De Beni, R., & Schellenberg, E. G. (2022). Music Listening, Emotion, and Cognition in Older Adults. ''Brain Sciences, 12''(11), 1567. <nowiki>https://doi.org/10.3390/brainsci12111567</nowiki> | |||
5. Särkämö, T. (Year). ''Music for the ageing brain: Cognitive, emotional, social, and neural benefits of musical leisure activities in stroke and dementia''. Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki. content | |||
6. Waugh, M., Youdan Jr., G., Casale, C., Balaban, R., Cross, E. S., & Merom, D. (2024). The use of dance to improve the health and wellbeing of older adults: A global scoping review of research trials. ''PLoS ONE, 19''(10), e0311889. <nowiki>https://doi.org/10.1371/journal.pone.0311889</nowiki> | |||
7. Segal, A. D., Adamczyk, P. G., Petruska, A. J., & Silverman, A. K. (2022). Hands-free balance therapy using robotic mobile feedback for home-based training for aging adults. ''IEEE Transactions on Neural Systems and Rehabilitation Engineering''. <nowiki>https://doi.org/10.1109/TNSRE.2022.3205850</nowiki> | |||
8. Zhao, D., Sun, X., Shan, B., Yang, Z., Yang, J., Liu, H., Jiang, Y., & Hiroshi, Y. (2023). Research status of elderly-care robots and safe human-robot interaction methods. ''Frontiers in Neuroscience'', ''17'', 1291682. <nowiki>https://doi.org/10.3389/fnins.2023.1291682</nowiki> | |||
== Planning (approach, milestones and deliverables) == | == Planning (approach, milestones and deliverables) == | ||
Revision as of 13:26, 13 February 2025
Group members
| Group member | Student number | Study program |
|---|---|---|
| Amélie van Rossum | 1743929 | BPT |
| Annika Valkering | 1890395 | BPT |
| Koen Jaartsveld | 1855786 | BPT |
| Lisa van Nuland | 1778528 | BPT |
| Max te Brake | 1534017 | BPT |
State-of-the-art
Problem statement and objectives
User description
Old people
User requirements
User requirements + articles
1. Low-impact dance movements for elderly users
Create dance programmes that include low-impact movements specifically designed for older users. Incorporate well-controlled ballet and tap dance movements that can be performed by the robot, focusing on arm, hand and head movements that the Pepper robot can demonstrate. With such an approach, older participants can perform the activities sitting or standing, improving their physical endurance, strength and functionality in a safe way. Movement that maintains flexibility and reduces pain does not increase the risk of injury, but has been shown to encourage very high levels of adherence among participants to demonstrate effectiveness and also something worth doing (Green et al., 2024). Including aspects of aerobics that reduce psychological stress and possible mood enhancement would be valuable, as indicated by a study in which low-impact aerobic dance exercises significantly improved stress levels among sedentary women in Malaysia (Johar et al., 2012).
2. Mood enhancement
Intermittent dance exercises
The robot should have intermittent aerobic dance exercises of light intensity (I-LADE) as its core activity. This exercise is considered the best to improve mood in older adults because it is very fun and engaging. According to a study published in 2021 in Frontiers in Aging Neuroscience, both forms of exercise interventions (continuous and intermittent) had a positive impact on mood and executive functions. However, the I-LADE (intermittent) intervention was particularly beneficial because it was more fun, which made it most likely to increase participation for longer. Participants reported that this intervention was clearly more pleasurable and enjoyable than continuous physical activity, allowing this intervention to be included fairly regularly in treatment programmes for older adults, especially as a morale booster (Frontiers in Aging Neuroscience, 2021).
Classical music
The robot should include classical music with a happy sound, specifically pieces by Mozart, to help improve the mood and cognitive functioning of elderly users. Such music would use the general inherent characteristics of classical compositions to evoke happiness and would therefore be suitable dancing programs to boost mood. Research suggests that listening to happy-sounding music, such as Mozart's, can significantly increase the level of arousal and mood in older people. This kind of music is not only good for mood but also for cognitive functions, working memory and skills needed for voluntary mental activity in older people to maintain overall mental health (Vincenzi et al., 2022).
Personalized music
Personalised music interventions could include using favourite genres and songs to improve mood in older users, especially those with stroke or dementia. The robot will facilitate music sessions that are personalised to evoke positive emotional responses that improve mood. Teppo Särkämö's research proves that personalised music, especially well-known and favourite songs, plays a crucial role in improving the mood and emotional well-being of elderly people. Such interventions take advantage of the very close emotional relationships users have with music they like, and activate positive memories and feelings that are exceptionally strong for improving mood. It emphasizes that familiar music evokes stronger emotional responses and activates reward circuits in the brain more effectively than unfamiliar music.
3. Customization of movement intensity to ensure safety and comfort for all users
The system should be able to adjust movement intensity and style so that all users, particularly older users, feel safe and comfortable. Older users may have varying levels of physical ability. Balance and type of movements should be modified to ensure the safety and comfort of the programme for older participants. This modification is due to the fact older individuals do not have comparable physical capabilities, as inscribed in the synthesis evidence from recent studies on health programmes in dance. Such customized approaches minimize injury risk in dance activities while promoting greater overall participation by making movements accessible and enjoyable for all participants, irrespective of their physical condition. (Waugh et al., 2024).
4. Hands-Free Controls
The robot must feature hands-free controls, such as voice commands, so that users with mobility or cognitive limitations can still use the robot. According to Zhao et al (2023), human-robot interaction, perception-based systems and prediction-based systems design to adapt to the user's needs while ensuring safety and comfort. Dance therapy is usually defined as artistic therapy, i.e. coordinated movements and balanced use of music; hands-free control allows the user to interact with the robot without diverting their attention or requiring manual input. In addition, voice controls also enable interaction where users can start, stop or tune dance routines without the burden of physical control input that can be difficult for those with less dexterity or cognitive limitations. Another advantage is that voice guidance can provide real-time encouragement, corrections or instructions that can increase motivation and support dance sessions. Psychological safety has also been shown to greatly aid user acceptance of robotic systems (Zhao et al., 2023). Letting users control the robot with words rather than by moving their body reduces worry and increases confidence, especially among people who are not so used to technology.
5. Clear visual and audio guidance
Research on interactive robotic feedback and balance therapy demonstrates that customized movement intensity, real-time feedback, and hands-free controls significantly improve adherence, engagement, and motor functions in older people (Segal et al., 2022).
Bibliography
1. Kimberly Lazo Green, Yang Yang, Ukachukwu Abaraogu, Claire H Eastaugh, Fiona R Beyer, Gill Norman, Chris Todd, Effectiveness of dance interventions for falls prevention in older adults: systematic review and meta-analysis, Age and Ageing, Volume 53, Issue 5, May 2024, afae104, https://doi.org/10.1093/ageing/afae104
2. Johar, M., Omar-fauzee, M. S., Abu Samah, B., & Abd Rashid, S. (2012). Effect of low-impact aerobic dance exercise on psychological health (stress) among sedentary women in Malaysia. Biology of Sport, 29(1). Effect_of_low-impact_aerobic_dance_exercise_on_psy.pdf
3. Frontiers in Aging Neuroscience. (2021). Comparison between the effects of continuous and intermittent light-intensity aerobic dance exercise on mood and executive functions in older adults. Retrieved from https://www.frontiersin.org/articles/10.3389/fnagi.2021.723243/full
4. Vincenzi, M., Borella, E., Sella, E., Lima, C. F., De Beni, R., & Schellenberg, E. G. (2022). Music Listening, Emotion, and Cognition in Older Adults. Brain Sciences, 12(11), 1567. https://doi.org/10.3390/brainsci12111567
5. Särkämö, T. (Year). Music for the ageing brain: Cognitive, emotional, social, and neural benefits of musical leisure activities in stroke and dementia. Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki. content
6. Waugh, M., Youdan Jr., G., Casale, C., Balaban, R., Cross, E. S., & Merom, D. (2024). The use of dance to improve the health and wellbeing of older adults: A global scoping review of research trials. PLoS ONE, 19(10), e0311889. https://doi.org/10.1371/journal.pone.0311889
7. Segal, A. D., Adamczyk, P. G., Petruska, A. J., & Silverman, A. K. (2022). Hands-free balance therapy using robotic mobile feedback for home-based training for aging adults. IEEE Transactions on Neural Systems and Rehabilitation Engineering. https://doi.org/10.1109/TNSRE.2022.3205850
8. Zhao, D., Sun, X., Shan, B., Yang, Z., Yang, J., Liu, H., Jiang, Y., & Hiroshi, Y. (2023). Research status of elderly-care robots and safe human-robot interaction methods. Frontiers in Neuroscience, 17, 1291682. https://doi.org/10.3389/fnins.2023.1291682
Planning (approach, milestones and deliverables)
Each week, there will be a mentor meeting on Monday morning to ask questions and get feedback. Furthermore, we have two additional group meetings every week, one directly after the mentor meeting and one on Friday during the break. The Wiki will be updated every Sunday (weekly deliverable).
On a weekly basis, we will evaluate what tasks need to be done and assign the tasks according to skills and interests of the group members.
Week 1
- Introduction to the course and forming of teams - all
- Brainstorm to come up with ideas for a project and select one - all
- Communicate the idea with the course coordinater - Annika
- Conduct literature review (5 pp) - all
- Write problem statement - Lisa
- Write objectives - Max
- Write user description - Amélie
- Write user requirements - Koen
- Make planning (containing approaches, milestones, deliverables) for the project - Annika
- Select technology (Pepper, other TU/e robot) - all
Week 2
- Confirmation to use the robot lab and which robot
- Create ERB form and get approval
- Create survey about mood for pre- and post-test
- Outline of capabilities of the robot
Week 3
- Program the robot
- Make consent form
- Start finding participants
Week 4
- Final arrangements for experiment set-up (milestone 1)
- Start with user testing/experiment
Week 5
- Finalize user testing/experiment (milestone 2)
- Analyze findings
Week 6
- Write results section
- Write discussion section
- Write conclusion section
Week 7
- Finalize report (milestone 3)
- Prepare final presentation + demo
- Give final presentation (milestone 4)
- Fill in peer review
Individual effort per week
| Group member | Total hours | Tasks |
|---|---|---|
| Amélie van Rossum | Intro lecture (2h), group meeting (1h) | |
| Annika Valkering | Intro lecture (2h), literature review (2h), Wiki layout and draft planning (2h), group meeting (1h) | |
| Koen Jaartsveld | Intro lecture (2h), group meeting (1h) | |
| Lisa van Nuland | Intro lecture (2h), literature review (2h), draft problem definition, user needs and approach (2h), group meeting (1h) | |
| Max te Brake | Intro lecture (2h), group meeting (1h) |
| Group member | Total hours | Tasks |
|---|---|---|
| Amélie van Rossum | ||
| Annika Valkering | ||
| Koen Jaartsveld | ||
| Lisa van Nuland | ||
| Max te Brake |
| Group member | Total hours | Tasks |
|---|---|---|
| Amélie van Rossum | ||
| Annika Valkering | ||
| Koen Jaartsveld | ||
| Lisa van Nuland | ||
| Max te Brake |
| Group member | Total hours | Tasks |
|---|---|---|
| Amélie van Rossum | ||
| Annika Valkering | ||
| Koen Jaartsveld | ||
| Lisa van Nuland | ||
| Max te Brake |
| Group member | Total hours | Tasks |
|---|---|---|
| Amélie van Rossum | ||
| Annika Valkering | ||
| Koen Jaartsveld | ||
| Lisa van Nuland | ||
| Max te Brake |
| Group member | Total hours | Tasks |
|---|---|---|
| Amélie van Rossum | ||
| Annika Valkering | ||
| Koen Jaartsveld | ||
| Lisa van Nuland | ||
| Max te Brake |
| Group member | Total hours | Tasks |
|---|---|---|
| Amélie van Rossum | ||
| Annika Valkering | ||
| Koen Jaartsveld | ||
| Lisa van Nuland | ||
| Max te Brake |
| Group member | Total hours | Result |
|---|---|---|
| Amélie van Rossum | ||
| Annika Valkering | ||
| Koen Jaartsveld | ||
| Lisa van Nuland | ||
| Max te Brake |