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Soft Robot for Elderly Fall Prevention
Falls are a significant healthcare concern affecting people aged 65 years and above. It has been estimated that one in four U.S. residents fall every year, which is often associated with serious injuries or even death (Burns & Kakara, 2018). According to Burns and Kakara (2018), the rate of deaths associated with falls increased by 30% during the past decade. The shortage of nursing staff and the increasing population can soon lead to the rise of the mortality rate related to falls.
Therefore, by addressing the problem, it is possible to improve peoples safety and reduce healthcare costs. Unmanned systems have been used in the health-related industry, and certain steps to develop fall prevention tools have been made (Zhang et al., 2017). However, there is still no effective unmanned system that could provide a viable solution to the problem. The proposed UGV will become a solution to a problem for the elderly living alone in their homes and those living in nursing homes.
The UGV in question will target nursing home residents and older people who live in their houses and are occasionally visited by their relatives or medical staff. The working name for the system is NoFallsRob, and it will be fully automated. The system will involve three major components: a charging base, sensor-based wearable device, and a soft robot that is similar to a walker. The proposed system will have sound and motion sensors that will activate the machine when needed.
When a person calls or starts moving the robot moves to the necessary spot. The user is informed about his helpers proximity by certain voice messages. NoFallsRob can be then employed as a walker, but its advantage is its complete focus on the position of the individual. This feature is specifically beneficial for those affected by dementia as these older people often fail to utilize their walkers, which leads to falls. The NoFallsRob always moves to the right place and ensures the persons safety.
The proposed system will be mainly charged with the help of the charging base, but it can also have some solar panels that could prolong its working hours. The functioning of outdoor NoFallsRobs can be facilitated by these panels. As mentioned above, the system will include a wearable device. The use of sensor-based wearable facilities has proved to be efficient in the healthcare setting, especially with older patients (Andrews & Raja, 2017).
This component will ensure the precision of the work of the system as the soft robot will respond to the exact persons movements. It will not be activated by other peoples movements or voices. However, it can be programmed to respond to a certain persons voice, which can be important for caregivers. The proposed system can also include some additional features, including but not confined to alarms, music, or even mobile-based connection.
In conclusion, the proposed UGV system will be instrumental in reducing the rate of falls among the elderly. The NoFallsRob can be helpful in nursing homes and households where older people live. The system is mainly electricity-powered, but it can also have solar panels. The new system will help in enhancing elderly peoples safety and reducing healthcare costs linked to unintentional injury. It will also help many elderly people become more confident and active, which will inevitably improve their overall health condition.
References
Andrews, L. J. B., & Raja, L. (2017). Remote based patient monitoring system using wearable sensors through online and offline mode for android based mobile platforms. In 2017 International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS) (pp. 602-606). Dubai, the United Arab Emirates: IEEE. Web.
Burns, E., & Kakara, R. (2018). Deaths from falls among persons aged e65 years United States, 20072016. MMWR: Morbidity and Mortality Weekly Report, 67(18), 509-514. Web.
Guirguis-Blake, J. M., Michael, Y. L., Perdue, L. A., Coppola, E., & Beil, T. (2018). Interventions to prevent falls in older adults. JAMA, 319(16), 1705-1716. Web.
Zhang, T., Li, Q., Zhang, C. S., Liang, H.W., Li, P., Wang, T., Li, S., & Wu, C. (2017). Current trends in the development of intelligent unmanned autonomous systems. Frontiers of Information Technology & Electronic Engineering, 18(1), 68-85. Web.
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