Internet of things gerontechnology for fall prevention in older adults: an integrative review

Diniz, Jamylle Lucas; Sousa, Viviane Ferreira; Coutinho, Janaína Fonseca Victor; Araújo, Ítalo Linhares de; Andrade, Rossana Maria de Castro; Costa, Joyce da Silva; Barbosa, Rachel Gabriel Bastos; Marques, Marilia Braga

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Review Article • Acta Paul Enferm 35 • 2022 • https://doi.org/10.37689/acta-ape/2022AR03142 copy

Internet of things gerontechnology for fall prevention in older adults: an integrative review

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Objective

To identify in the literature the Internet of Things gerontechnology developed to prevent accidents by falls in older adults.

Methods

This integrative review was carried out from January to May 2020. Articles without period or language restriction with individuals aged 60 years or older addressing the use of Internet of Things gerontechnology for fall prevention were included. Duplicate articles were excluded. The search was performed by the PIE strategy (Population, Intervention, Effect/Assessment), resulting in the question: “What Internet of Things gerontechnology developed for accident prevention by falls in older adults available in the literature?”. It was performed in the MEDLINE/PubMed, LILACS, CINAHL, Scopus and Web of Science databases. Year, type of study, country, professionals involved, outcome, development site and classification in Internet of Things gerontechnology and prototypes were identified.

Results

Twenty-three Internet of Things gerontechnology were identified. The years 2018 and 2019 had higher numbers of publications. There was a predominance of descriptive studies by computer science professionals and engineers and developed in Europe, Asia, North America and Oceania. Eight Internet of Things gerontechnology and 15 prototypes were found, seven sensors, five devices, three serious games and systems, two robots and one exergames, virtual reality and application. Most gerontechnology sought to improve mobility and balance, five of which were developed in the hospital and home environments, respectively.

Conclusion

The Internet of Things gerontechnology can be used as resources to assist in fall prevention and strengthening functional capacity. However, future research is needed to analyze the effectiveness of this type of technology for fall prevention in older adults.

Aged; Internet of things; Technology; Accidental falls; Accident prevention

Component	Search terms		Search strategy	Databases
Component	Uncontrolled descriptors	Controlled descriptors	Search strategy	Databases
P: Population	Elderly; Old; Elder; Aging	Aged	(Gerontechnology OR Technology OR Internet of Things) AND (Elderly OR Old OR Elder OR Aged OR Aging) AND Prevention AND Accidents Fall;	MEDLINE/PubMed LILACS CINAHL Web of Science SCOPUS
I: Intervention	Gerontechnology	Technology; Internet of Things
E: Effect/Assessment	Prevention	Accidents Fall

IoT gerontechnology
Year/Country/Citation	Specifications	Description	Main findings
Aidemark et al. 2019/ Sweden ⁽³⁴⁾	System- Fall management with advice, sensors and app.	Combination of preventive actions through expert advice and examples of risks, detection of fall incidents with sensors that capture body movements, visual detection of the user’s movement and position, analysis of behavior patterns.	IoT-oriented home learning environment for fall prevention that makes living independently and enhanced self-understanding to make everyday life easier. Developed in a home environment.
Aljahdali et al., 2018/ Algeria ⁽³⁵⁾	System – Intelligent assistive walker device for the visually impaired and older adults.	Hardware and software device. Hardware consisting of sensor, controller and output. Software composed by the “Map” and “Find-me” apps. The information received from the sensors (position, objects and people around) are sent to commands to the controller and guide the walker to meet the needs of older adults safely.	Recognize the dangerous positions that can cause the fall. Developed in a home environment.
Jähne-Raden et al., 2019/ Germany ⁽³¹⁾	INBED System	The wearable component attaches to older adults’ upper leg in the upper half of the thigh, ideal for detecting lifting events by changing the angle of the legs without affecting comfort. In addition to the sensor, the developed system contains relay stations and a central signal processing base station to create a scalable communication network.	System supports professional care in reducing patient injuries caused by falls. Developed in a hospital environment.
Kouris et al., 2015/ Serbia ⁽⁴³⁾	Game – KINOPTIM: Game platform that provides the medical profile of each individual to develop a Personalized Clinical Decision Support System (PCDSS).	During the execution of the exercises, wearable sensors are placed on the wrists and ankles to detect movement; then, the MBI module incorporates a Decision Support System (DSS) to collect, organize and analyze the passive, active and cooperative relationships of the collected data. The DSS used in the KINOPTIM platform receives as input the medical profile of each individual to develop a Personalized Clinical Decision Support System (PCDSS).	Classifies fall risk levels and generates recommendations for physicians. Developed in a home environment.
Torres et al., 2016/ Australia ⁽²³⁾	Sensor - WISP battery-free wearable sensor with radio frequency identification (RFID).	Battery-free wearable sensor for use over clothing prior to the sternum, in which there is data corresponding to the movements and identification being collected in real time via RFID. Data is received at the bed and chair exit recognition stage for processing and analysis. Thus, an alert can be issued to caregivers when leaving the bed or chair.	Determining bed and chair outputs in real time is important due to the lack of methods in the literature that use batteryless sensors for fall prevention. Developed in a hospital environment.
Wolf et al., 2013/ Germany ⁽³²⁾	Sensor - Bed exit alarm.	Shimmer sensors available at the bedside and equipped with Bluetooth. Prototype integrates wide motion protection as a precursor to bed exit and protection from high acceleration during fall.	Reliably detects attempts to get out of bed and generates few false alarms. Developed in a hospital environment.
Ranasinghe et al., 2012/ USA ⁽²⁶⁾	Sensor - WISP: Wireless identification and detection platform through a wearable sensor.	Wireless identification and detection of the WISPs Platform (wearable device) for real-time monitoring and identification of activities: 1) RFID readers; 2) Monitoring software.	Great potential to provide a technological intervention to prevent falls in hospitals. Developed in a hospital environment.
Hilbe et al., 2010/ Austria ⁽³³⁾	-BUCINATOR sensor: bed exit alarm.	Air-filled pressure sensitive rails are mounted on the top edge of the bed side rail for the exit alarm system. These rails are connected with the pressure sensor. If a patient at risk of falling intends to get out of bed with the siderail in the upright or lowered position, pressure in the system increases and if a threshold level is exceeded, an electrical alarm signal is generated. The nursing staff will be informed about the risk of the situation through the public address system.	A reliable bed exit alarm system gives confidence in relatives’ safety and puts less strain on the family. Developed in a hospital environment.
IoT gerontechnology prototypes
Year/Country/Citation	Specifications	Description	Main findings
Patton et al., 2008/USA.⁽²⁷⁾	Robot - KineAssist for gait and balance training.	Provides partial body weight support and postural control; allows movement of the trunk and pelvis; follows ground walking movements in forward, rotation, and avoidance directions; and makes it impossible for the individual to lose balance.	It can help prevent falls, as it improves gait and balance. Does not mention the location of development.
Merilampi et al., 2019/ Finland⁽³⁸⁾	Exergame - based on a smart chair.	Developed for Android devices via Bluetooth. User movements are measured by nine pressure sensors located under the chair seat. Sensors send their data to the Android device. The exergame “smart chair” uses three categories of minigames: ski jumping, snowboarding and ball tossing. Interaction with the game environment requires the user to move their body. The snowboard minigame is designed to train postural control in a seated position. The ski jumping minigame requires greater functional skill. The ball toss game incorporates upper extremity strength and coordination.	Facilitates the delivery of fun tools in providing preventive interventions with the potential to decrease the risk of falling. Does not mention the location of development.
Prasertsakul et al., 2018/ Thailand⁽²⁹⁾	Game - Dual Task Virtual Reality Balancing Training (DTVRBT).	Laptop and Kinect sensor. The 3D information from this sensor allows users to interact with the object in the virtual environment (Unity3D). The game requires arm movement in both vertical and horizontal directions. The player must place the object in the assigned area.	It can facilitate better postural control and contribute to fall prevention of healthy adults in the future. Does not mention the location of development.
Verrusio et al., 2017/ Italy ⁽⁴²⁾	-Human Body Posturizer (HBP) device	Device composed of articulated orthosis, with four elements that come into contact with different anatomical zones, being able to adapt to the physical characteristics of each individual. Improves the accuracy of the response, walking and posture, stimulating the prefrontal cortex (PFC), fundamental in motor control.	Useful tool for fall prevention in older adults, as it reduces risk factors in older adults with chronic conditions. Developed in a geriatric institution.
Viriyavit et al., 2020/ United Kingdom⁽⁴¹⁾	Sensor - Alarm for bed exit detection	Sensor panel equipped with two types of sensors to detect the weight applied to the bed, being installed on the left and right side of the panel. The combination of the two pairs of different types of sensors is used to detect the position of each side of the body on the bed.	It works with high accuracy in position detection and requires fewer sensors than other existing ones. Does not mention the location of development.
Raffe et al.,/ 2018/ Australia ⁽²⁴⁾	Virtual Reality - Kinect + HTC Vive – Simple setup that combines skeletal tracking and virtual reality.	Kinect: Track the player’s body movement. HTC Vive: used for virtual reality screen.	It has the potential to increase the immersion of an experience and prevent potential falls. Does not mention the location of development.
Tzung-Han et al., 2017/ Taiwan ⁽⁴⁵⁾	Device - Fall prevention shoes	Line laser on the side of the shoes and RGB camera on the upper part of the shoes. System sends alert according to the width and depth of the detected obstacles.	Suitable to be installed on portable devices and general product costs are acceptable Does not mention the location of development.
Di P et al., 2016/ Japan ⁽³⁹⁾	Device - Smart Cane	Robot consisting of a unidirectional mobile base, aluminum pole, minicomputer, sensor system and a laser rangefinder (LRF), used to assist older adults in walking training.	Behaves to prevent the user from being in a position to generate falls. Does not mention the location of development.
Vieira et al., 2015/ Portugal ⁽⁴⁰⁾	Game - based on the Berg Balance Scale (BBS) test	Game association + BBS-based motion sensor consisting of daily tasks exercises. And the sensors are used to detect movement, correctly distinguishing between activities of daily living, such as sitting or walking, from an actual fall duration.	Improves autonomy and safety, specifically for those at risk of falling. Developed in a home environment.
Maneeprom et al., 2019/ Thailand ⁽³⁰⁾	Robot	8-inch touch screen attached to the head of a Dinsow Mini robot version M2070, where older adults watch four videos on fall prevention and choosing walking aid devices, two videos on suitable footwear, two videos on exercise and 28 voice messages about fall prevention and daily exercise reminder.	It increases knowledge about fall prevention, promotes exercise, and improves balance between physically active and at-risk older adults. Developed in a home environment.
Qiu et al., 2018 / South Korea ⁽³⁷⁾	Sensors -A set of miniature wearable inertial sensors	Inertial sensors are placed on the lower back, thighs and legs and a battery of tests performed for a multifactorial fall risk assessment is performed to identify the greatest number of risk factors presented.	Wearable inertial sensor-based systems show great promise for the assessment of fall prevention in older adults. Does not mention the location of development.
Wu et al., 2018/ Canada ⁽³⁶⁾	Sensor - Wearable sensor-based fall risk assessment program (SFRA).	SFRA consists of two core pieces: a wearable device for collecting and storing data and a mobile device for displaying fall hazard information.	Information can motivate older adults to adopt fall prevention interventions. Does not mention the location of development.
Moufawad et al., 2016/ Switzerland ⁽⁴⁴⁾	Instrumented-Shoes Device	The system consists of the Physilog inertia detection and data logging unit and the plantar pressure insole. Its architecture is oriented to collect real-time footwear data and perform online activity classification and characterization (eg gait analysis of locomotion periods and postural transition analysis). Data from all sensors (medial and lateral heel, lateral arch, 1st / 3rd / 5th metatarsals, hallux and remaining toes) are stored on a memory card to prevent data loss. .	Assesses mobility and provides quick, personalized feedback for older adults. Developed in a geriatric institution.
Goulding et al.,2015 USA ⁽²⁸⁾	Application - Sparrow system.	Mobile application for Android connected to sensors and attached to a wheelchair that emits movement signals warning of the risk of falling.	Efficient to issue real alerts about user movement during use. Does not mention the location of development.
Qiu et al., 2013/ Australia ⁽²⁵⁾	Device - Textured Insoles	Insoles inserted into standard shoes to reduce postural sway.	Improves stability and reduces postural sway. Does not mention the location of development.

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[1] Corresponding author: Jamylle Lucas Diniz E-mail: jamylledz@hotmail.com