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Can flexible IoT walkers effectively reduce the risk of falls among seniors? 

STRIDE
Scopus
Accelerometer
Wearable computer
Gait
Best insight from top research papers

Flexible IoT walkers can significantly contribute to reducing the risk of falls among seniors by integrating advanced technologies that monitor and support the elderly's mobility. The development of skin-wearable electronic devices for motion sensing, as discussed by Yongkuk Lee et al., demonstrates the potential of IoT technologies in accurately detecting falls, which is crucial for preventing them among older adults . Similarly, the use of IoT for enhancing the safety of the elderly, as reviewed by Sara Dorri et al., shows that such technologies, including motion sensors, have shown promising results in ensuring the safety of this vulnerable population . The clinical validation of the G-STRIDE system, which assesses gait and balance through a 6-axis inertial measurement unit, further underscores the effectiveness of IoT devices in identifying individuals at risk of falling by analyzing walking-related metrics . Moreover, the integration of fall detection systems into smartphones using IoT methods, as implemented by Swati Sikdar et al., highlights the adaptability and accessibility of such technologies in real-life conditions, making them a practical solution for monitoring seniors . The novel approach of embedding smart devices in walking canes for detecting abnormal gait and tremors, as introduced by Marion O. Adebiyi et al., represents an innovative and non-intrusive method of early disease detection and fall prevention . Additionally, the proposal of a non-wearable IoT solution for fall detection in homes by Osvaldo Ribeiro et al. emphasizes the potential of ambient technologies in providing a safety net for the elderly without the need for active user engagement . The development of an electronic system integrated into a walking stick, as contemplated by Shaik Ahmadsaidulu et al., combines multiple functionalities, including fall detection and obstacle avoidance, offering a comprehensive tool for enhancing the mobility and safety of visually impaired and elderly individuals . The research on gait training devices by Katsushi Ogawa et al. further illustrates the role of IoT in rehabilitating gait function, thereby preventing falls by improving the physical capabilities of the elderly . The Automated Disabled People Fall Detection model developed by Mesfer Al Duhayyim, which utilizes AI and IoT for distinguishing fall events, showcases the high accuracy and potential of technology-driven solutions in fall prevention . Lastly, the wearable system proposed by Flora Amato et al., which employs sensors and neural networks for real-time movement identification and fall detection, highlights the effectiveness of portable and responsive IoT devices in mitigating fall risks among seniors . In conclusion, the integration of flexible IoT technologies, ranging from wearable devices to ambient systems and smart canes, offers a promising approach to effectively reduce the risk of falls among seniors by providing continuous monitoring, early detection of fall risks, and support for mobility and balance.

Answers from top 4 papers

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Papers (4)Insight
Open access•Journal Article•DOI
The Application of Internet of Things for the Elderly Health Safety: A Systematic Review
Sara Dorri, Hedieh Zabolinezhad, Mohammadamin Sattari 
27 Apr 2023-Advanced Biomedical Research
Not addressed in the paper.
Open access•Journal Article•DOI
Experimental Study: Deep Learning-Based Fall Monitoring among Older Adults with Skin-Wearable Electronics
Yongkuk Lee, Suresh Pokharel, KC DukkaB., Kyoung Hag Lee, Woon-Hong Yeo 
01 Apr 2023-Sensors
Not addressed in the paper.
Open access•Journal Article•DOI
Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor
M. Neira Álvarez, Antonio R. Jimenez Ruiz, Elisabet Huertas-Hoyas, A. del-Ama, Luisa Ruiz-Ruiz, Sara Garcia-de-Villa, Cristina Rodriguez-Sanchez 
06 Jun 2023-Dental science reports
The G-STRIDE foot-mounted inertial sensor, a flexible IoT walker, effectively assesses fall risk in seniors by measuring walking parameters correlated with clinical markers, potentially reducing falls.
Open access•Journal Article•DOI
Design & Development of a Cost-Effective User-Friendly Fall Detection Device Using IOT Technology
Swati Sikdar, Swarnendu Maity, Dipayan Mondal, Sourav Saha 
13 Mar 2023-Indian Scientific Journal Of Research In Engineering And Management
Not addressed in the paper.

Related Questions

Issues on iot adoption for elderly5 answersIssues related to IoT adoption for the elderly include challenges in pre-adoption of smart home services, lack of information on smart home technology capabilities, high costs, platform management, infrastructure concerns, and privacy issues. Elderly individuals face health problems requiring constant assistance, leading to dependency, while also desiring independence. To address these challenges, innovative solutions like the Cyborg robot have been developed to assist the elderly in daily activities within smart home environments, utilizing technologies such as the k-nearest neighbors with an artificial bee colony algorithm for efficient control of electronic appliances and intruder detection. Despite positive attitudes towards smart homes for safety and independent living, there is a need for better understanding of older adults' perspectives to enhance IoT-based smart home services adoption.
How can wearable technology be designed to improve mobility and balance in elderly individuals?5 answersWearable technology can significantly enhance mobility and balance in elderly individuals by incorporating features like physiological monitoring, fall detection, and remote health status tracking. These devices utilize various technologies such as sensors, intelligent algorithms, wireless communication modules, and automatic voice recognition to monitor vital signs, detect falls, and provide real-time health data to caregivers. Specifically, smart wearable devices based on the Internet of Things and ARM architecture offer functionalities like temperature monitoring, sleep tracking, electronic fencing, and blood oxygen level monitoring to ensure comprehensive care and safety for the elderly. By integrating these advanced features, wearable technology can empower seniors to maintain independence while enabling their families to remotely monitor and ensure their well-being.
Fall detection in older adults with mobile IoT?5 answersFall detection in older adults with mobile IoT is an important area of research. Several studies have proposed systems for fall detection using wearable devices equipped with accelerometers and gyroscopes to determine the user's postures and behavior states, such as standing, sitting, walking, lying down, and falling. These systems aim to recognize and report fall events in real-time, reducing the response time of caregivers and allowing for immediate intervention. Additionally, the integration of IoT and smart speakers can be used to verify whether a fall has occurred by asking the smart speaker. Edge computing-based fall detection systems have also been developed, utilizing accelerometer sensor data and artificial intelligence software to achieve high recognition accuracy. These systems provide cost-effective and user-friendly solutions for early detection and prevention of falls in older adults. Overall, the combination of wearable devices, IoT, and edge computing technologies shows promise in improving fall detection and ensuring the safety of older adults.
IoT AND fall AND elderly AND community?5 answersThe Internet of Things (IoT) has been applied to fall detection systems for the elderly community. Various technologies and sensors, such as gyroscopes and accelerometers, have been used to detect falls and differentiate them from daily activities. These systems aim to provide real-time monitoring and prompt assistance to reduce the severity of falls and improve patient outcomes. Wearable IoT devices, such as smartphones and smartwatches, have been integrated with fall detection algorithms to create affordable and non-invasive solutions. Additionally, the use of artificial intelligence (AI) techniques, including machine learning and deep learning models, has been explored to automate fall detection and improve accuracy. The development of IoT-enabled systems for fall detection in the elderly holds promise for remote monitoring and timely intervention to ensure their safety and well-being.
What interventions can be used to reduce the risk of falls in the elderly?5 answersExercise interventions and home fall-hazard reduction interventions have been shown to be effective in reducing the risk of falls in the elderly. Exercise interventions, including various types of exercises, can reduce the rate of falls by 26% and slightly reduce the number of people experiencing falls by 10% in people with mild to moderate Parkinson's disease (PD). Home fall-hazard reduction interventions, which involve identifying and assessing fall hazards in the home, can reduce the rate of falls by 26% and the proportion of older people who have one or more falls by 11% in community-residing older people. These interventions should be part of a comprehensive fall prevention care plan, which may also include assistive technology interventions, education interventions, and home modifications. Further research is needed to explore the effectiveness of other interventions and to determine the impact of different types of exercise and levels of supervision on falls in the elderly.
What are the most effective interventions to prevent falls in the elderly?5 answersExercise, including moderate to high intensity balance training, is an effective strategy for preventing falls in older people. Multifactorial interventions, which are tailored to identified risk factors, are also effective in high-risk populations. Other successful interventions include enhanced podiatry, home safety interventions, expedited cataract extraction, cardiac pacing for people with carotid sinus hypersensitivity, and vitamin D supplementation in people living in care homes. In addition, the use of new technologies such as devices and software programs shows promise for low-cost and sustainable fall prevention interventions. Cholinesterase inhibitors may also reduce the rate of falls in people with Parkinson's disease, although the effect on the number of people falling is uncertain. Individualized fall prevention programs can decrease fear of falls and have a positive impact on preventing falls in elderly and senile patients.

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