Empowering Active and Healthy Ageing: Integrating IoT and Wearable Technologies for Personalised Interventions
Abstract
:1. Introduction
2. Materials and Methods
2.1. System Architecture
- Older Adults: The platform is specifically designed to be used by all adults who are older than 65 years [10]. Due to the main objectives of this experimentation (feasibility of home-based use of the solution and usability testing), requiring a most objective feedback from testers, the participants were recruited from able-bodied people, with no severe physical- or cognitive-related disability nor presenting severe mood disorders.
- Formal Caregiver: They are caregivers who have undergone specific training and certification to provide professional care services to those who require assistance [11]. They work in various healthcare settings, such as hospitals, nursing homes, and assisted living facilities.
Algorithm 1 Calculate Step Count Algorithm |
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2.2. Workflow and Intervention Delivery
2.3. Data Collected by Wearables
- Steps Count: Measures the number of steps taken daily. These data help in assessing the physical activity levels of the older adults.
- Heart Rate: Monitors heart rate variability to assess cardiovascular health. Continuous heart rate monitoring provides insights into the user’s physical condition and can detect irregularities early.
- Standing Up Frequency: Tracks how often users stand up, indicating their level of mobility and activity. Frequent standing up can be an indicator of higher activity levels and better physical health.
- Interactions with AGAPE Assistant: Logs interactions with the mobile app to monitor engagement and usability. These data are crucial for understanding how often and in what ways users are engaging with the technology.
3. Results
3.1. Wearable Sensor Deployment
3.2. OA Profiling
- Effort Expectancy: Perception of the ease of using technology.
- Performance Expectancy: Expectation of the benefits and effectiveness of using technology.
- Social Influence: Influence of social factors (family, friends or trusted people) on technology adoption decisions.
- Perceived Ubiquity: Perception of the availability and prevalence of technology in daily life.
- Self-Efficacy: Confidence in one’s ability to successfully use technology.
- Privacy Concerns: Concerns about the privacy and security implications of using technology.
- Intention to Adopt: Willingness and readiness to adopt and use technology.
- Anxiety: Feelings of unease or discomfort associated with using technology.
- Facilitating Conditions: Perception of the availability of resources and support to use technology effectively.
- Attitude toward Technology: Overall disposition and feelings toward technology usage.
3.3. AGAPE Assistant
- Simplified Navigation and Large Icons: The AGAPE Assistant features a user-friendly navigation system that includes prominently displayed icons that are easy to identify. This design decision facilitates the navigation of the programme for older folks, particularly those with little digital literacy, by providing them with a user-friendly and intuitive experience. The application features a fixed button located below the content, which has been found to be the most efficient method of navigating in an app for the OA [25].
- High Contrast and Readable Text: The app employs high-contrast colour palettes and utilises large, legible fonts to cater to users with visual impairments. This guarantees that the content is readily legible, hence minimising eye fatigue and enhancing the app’s accessibility.
- Intuitive Layout: The layout of the AGAPE Assistant is designed to be intuitive, with a clear hierarchy of information. Important functions and features are prominently displayed, reducing the cognitive load on users and making it easier for them to find what they need.
- Integration with SeniorPhone App: For users with very low digital literacy, the integration of the SeniorPhone app transforms the traditional Android launcher into a simplified, user-friendly interface. This feature includes large icons, easy navigation, high-contrast colours, and direct access to essential functions like calls, messages and emergency contacts.
3.3.1. Challenges and Adaptations
3.3.2. Usability Assessment of AGAPE Assistant
3.3.3. Technostress Assessment towards Wearables and AGAPE Assistant
3.3.4. Heuristic Evaluation
3.3.5. Short form User Experience Questionnaire (SUEQ)
- Obstructive vs. Supportive: This dimension assesses whether users perceive the technology as hindering or facilitating their tasks and activities. Higher scores indicate a more supportive experience, suggesting that users find the technology helpful rather than obstructive.
- Complicated vs. Easy: This dimension gauges the perceived complexity of the technology. Higher scores indicate that users find the technology easy to use and understand, while lower scores suggest a more complicated interface or system.
- Inefficient vs. Efficient: This dimension evaluates the perceived efficiency of the technology in assisting users with their goals. Higher scores indicate that users perceive the technology as effective and efficient in supporting their activities.
- Confusing vs. Clear: This dimension assesses the clarity and comprehensibility of the technology. Higher scores indicate that users find the technology clear and easy to follow, while lower scores suggest confusion or ambiguity in its usage.
- Boring vs. Exciting: This dimension measures the level of engagement and excitement elicited by the technology. Higher scores suggest that users find the technology engaging and stimulating, while lower scores indicate a lack of interest or excitement.
- Not interesting vs. Interesting: This dimension further evaluates the level of interest sparked by the technology. Higher scores indicate that users find the technology interesting and engaging, while lower scores suggest a lack of interest or novelty.
- Conventional vs. Inventive: This dimension assesses whether users perceive the technology as conventional or innovative. Higher scores suggest that users perceive the technology as innovative and inventive, offering new and creative solutions to their needs.
- Usual vs. Leading Edge: This dimension evaluates whether users perceive the technology as standard or cutting-edge. Higher scores indicate that users perceive the technology as advanced and at the forefront of its field.
3.4. AGAPE Monitor
3.4.1. Real-Time Monitoring and Analysis
3.4.2. Personalised Care Planning
3.4.3. Communication and Social Engagement
3.4.4. Outcome Reporting
3.5. Main Findings
4. State of Art and Discussion
4.1. Related Work
4.2. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
OA | Older Adult |
IoT | Internet of Things |
AGAPE | Connected Health and Social Engagement Framework for Technology Adoption |
IMU | Inertial Measurement Unit |
Appendix A
Appendix B
Date | Steps | Heart Rate (bpm) | Standing Up Frequency | Interactions with AGAPE Assistant |
---|---|---|---|---|
1 April 2023 | 5678 | 72 | 8 | 15 |
2 April 2023 | 6210 | 75 | 10 | 18 |
3 April 2023 | 4832 | 70 | 7 | 12 |
4 April 2023 | 7350 | 78 | 12 | 20 |
5 April 2023 | 4980 | 74 | 9 | 16 |
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Profile Name | Description | Number of OA |
---|---|---|
A1 | Low digital literacy and unfamiliar with technological tools like mobile application and wearables. These OAs might exhibit some suspicion and fear towards new technology. | 15 |
A2 | OAs already own a smartphone and have basic digital skills. For example, they can emit and receive phone calls on full autonomy. These OAs might exhibit some concerns regarding the integration of wearables and new technologies for health monitoring. | 50 |
B1 | Moderate to high digital skills and daily use of their smartphones. They usually have positive attitudes towards the use of the new technology and perceives these technologies as a game-changer for improving their health conditions. | 43 |
B2 | Very high digital literacy and have already integrated wearables or other health monitoring devices in their lifestyle. They can operate most technological tools and even perform some advanced procedures on full autonomy. For example, resetting and reconnecting a wearable. | 4 |
Solution | Health Monitoring | Activity Tracking | Social Interaction | Personalization | User Profiling |
---|---|---|---|---|---|
Iranpak et al. [30] | X | ||||
Liu et al. [31] | X | X | |||
Awadalla et al. [33] | X | X | |||
Stavrotheodoros et al. [34] | X | ||||
Lorusso et al. [35] | X | X | |||
Rojo-Perez et al. [37] | X | X | |||
Michèle et al. [38] | X | X | X | ||
Morrow-Howell et al. [39] | X | X | X | ||
Cristiano et al. [40] | X | X | |||
D’Onofrio et al. [41] | X | X | X | ||
Liu et al. [42] | X | X | X | ||
Nebeker et al. [43] | X | X | |||
Spinsante et al. [44] | X | X | X | X | X |
Lin et al. [45] | X | X | |||
Chaparro et al. [46] | X | X | |||
Hvalic-Touzery et al. [47] | X | X | |||
Talukder et al. [48] | X | X | X | ||
AGAPE Platform | X | X | X | X | X |
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Joymangul, J.S.; Ciobanu, I.; Agnoloni, F.; Lampe, J.; Pedrini, C.; Pinto, A.; Franceschini, B.; Nicolas, D.; Tamburini, E.; Cecchi, F.; et al. Empowering Active and Healthy Ageing: Integrating IoT and Wearable Technologies for Personalised Interventions. Appl. Sci. 2024, 14, 4789. https://doi.org/10.3390/app14114789
Joymangul JS, Ciobanu I, Agnoloni F, Lampe J, Pedrini C, Pinto A, Franceschini B, Nicolas D, Tamburini E, Cecchi F, et al. Empowering Active and Healthy Ageing: Integrating IoT and Wearable Technologies for Personalised Interventions. Applied Sciences. 2024; 14(11):4789. https://doi.org/10.3390/app14114789
Chicago/Turabian StyleJoymangul, Jensen Selwyn, Ileana Ciobanu, Francesco Agnoloni, Jure Lampe, Chiara Pedrini, Angela Pinto, Bruna Franceschini, Damien Nicolas, Elena Tamburini, Francesca Cecchi, and et al. 2024. "Empowering Active and Healthy Ageing: Integrating IoT and Wearable Technologies for Personalised Interventions" Applied Sciences 14, no. 11: 4789. https://doi.org/10.3390/app14114789
APA StyleJoymangul, J. S., Ciobanu, I., Agnoloni, F., Lampe, J., Pedrini, C., Pinto, A., Franceschini, B., Nicolas, D., Tamburini, E., Cecchi, F., Berteanu, M., & Khadraoui, D. (2024). Empowering Active and Healthy Ageing: Integrating IoT and Wearable Technologies for Personalised Interventions. Applied Sciences, 14(11), 4789. https://doi.org/10.3390/app14114789