Use of assistive devices in daily activities among 85-year-olds living at home focusing especially on the visually impaired

2004 ◽  
Vol 26 (24) ◽  
pp. 1423-1430 ◽  
Author(s):  
S Dahlin-Ivanoff ◽  
U Sonn
Keyword(s):  
Visually Impaired ◽  
Assistive Devices ◽  
Daily Activities ◽  
At Home

MAGIC-I as Assistance for the Visually Impaired People

2020 ◽  
Vol 13 ◽  
Author(s):  
Kavita Pandey ◽  
Dhiraj Pandey ◽  
Vatsalya Yadav ◽  
Shriya Vikhram
Keyword(s):  
Visually Impaired ◽  
Smart Phone ◽  
Emergency Situation ◽  
Daily Activities ◽  
Daily Life Activities ◽  
Best Friends ◽  
Visually Impaired People ◽  
The World ◽  
Impaired People ◽  
Impaired User

Background: According to the WHO report, around 4.07% of the world's population is visually impaired. About 90% of the visually impaired users live in the lower economic strata. In the fast moving technology, most of the invention misses the need of these people. Mainly the technologies were designed for mainstream people; visually impaired people always find an inability to access it. This inability arises primarily for reasons such as cost, for example, Perkins Brailler costs 80-248 dollars for the simple purpose of Braille input. Another major reason is the hassle of carrying the big equipment. Objective: Keeping all this in mind and making technology as their best friends, MAGIC-1 has been designed. The goal is to provide a solution in terms of an application, which helps the visually impaired user in their daily life activities. Method: The proposed solution assists visually impaired users through smart phone technology. If visually impaired users ever wished to have a touched guide into a smart phone, MAGIC-1 has the solution that consolidates all the important features in their daily activities. Results: The performance of the solution as a whole and its individual features in terms of usability, utility and other metrics, etc. has been tested with sample visually impaired users. Moreover, their performances in term of Errors per Word and Words per Minute have been observed. Conclusion: MAGIC-I, the proposed solution works as an assistant of visually impaired users to overcome their daily struggles and stay more connected to the world. A visually impaired user can communicate via their mobile devices with features like eyes free texting using braille, voice calling etc. They can easily take help in an emergency situation with the options of SOS emergency calling and video assistance.

scholarly journals Identifying Fall Risk Predictors by Monitoring Daily Activities at Home Using a Depth Sensor Coupled to Machine Learning Algorithms

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1957
Author(s):  
Amandine Dubois ◽  
Titus Bihl ◽  
Jean-Pierre Bresciani
Keyword(s):  
Machine Learning ◽  
Fall Prevention ◽  
Fall Risk ◽  
Learning Algorithms ◽  
Step Length ◽  
Machine Learning Algorithms ◽  
Daily Activities ◽  
Sitting Time ◽  
Behavioral Parameters ◽  
At Home

Because of population ageing, fall prevention represents a human, economic, and social issue. Currently, fall-risk is assessed infrequently, and usually only after the first fall occurrence. Home monitoring could improve fall prevention. Our aim was to monitor daily activities at home in order to identify the behavioral parameters that best discriminate high fall risk from low fall risk individuals. Microsoft Kinect sensors were placed in the room of 30 patients temporarily residing in a rehabilitation center. The sensors captured the patients’ movements while they were going about their daily activities. Different behavioral parameters, such as speed to sit down, gait speed or total sitting time were extracted and analyzed combining statistical and machine learning algorithms. Our algorithms classified the patients according to their estimated fall risk. The automatic fall risk assessment performed by the algorithms was then benchmarked against fall risk assessments performed by clinicians using the Tinetti test and the Timed Up and Go test. Step length, sit-stand transition and total sitting time were the most discriminant parameters to classify patients according to their fall risk. Coupling step length to the speed required to stand up or the total sitting time gave rise to an error-less classification of the patients, i.e., to the same classification as that of the clinicians. A monitoring system extracting step length and sit-stand transitions at home could complement the clinicians’ assessment toolkit and improve fall prevention.

Major Metrics, Concerns, and Assessment Strategy for Mobility Assistive Devices

2020 ◽  
pp. 171-203
Author(s):  
Yiannis Koumpouros
Keyword(s):  
Literature Review ◽  
The Elderly ◽  
Assistive Devices ◽  
Daily Activities ◽  
Assistive Device ◽  
Mobility Devices ◽  
Mobility Aids ◽  
Environmental Causes ◽  
Elderly Mobility

The ageing of the population is one of the major societal and financial problems. The prevalence of disability increases dramatically by age. The loss of mobility can be devastating to the elderly. Mobility aids are a one-way street to maintain independent mobility. The performance of daily activities is restrained by a series of factors related to the assistive device limitations, or the ones emerged from environmental causes. A literature review reveals minimal tools for assessing mobility assistive devices able to capture users' satisfaction. The chapter presents an assessment methodology in order to investigate assistive mobility devices' limitations, dissatisfaction reasons, and identifies the most appropriate tools to study such limitations and conclude in valid outcomes. One of the valuable characteristics of the study presented in its generalizability since it is not disease oriented. A summary of the results from both the literature review and the real case study on a mixed group of end users are presented in the chapter.

Mesh Network of eHealth Intelligent Agents for Visually Impaired and Blind People

2022 ◽  
pp. 240-271
Author(s):  
Dmytro Zubov
Keyword(s):  
Intelligent Agents ◽  
Visually Impaired ◽  
Assistive Devices ◽  
Mesh Network ◽  
Assistive Device ◽  
Raspberry Pi ◽  
Industrial Facilities ◽  
Blind And Visually Impaired ◽  
Wide Range ◽  
Human Faces

Smart assistive devices for blind and visually impaired (B&VI) people are of high interest today since wearable IoT hardware became available for a wide range of users. In the first project, the Raspberry Pi 3 B board measures a distance to the nearest obstacle via ultrasonic sensor HC-SR04 and recognizes human faces by Pi camera, OpenCV library, and Adam Geitgey module. Objects are found by Bluetooth devices of classes 1-3 and iBeacons. Intelligent eHealth agents cooperate with one another in a smart city mesh network via MQTT and BLE protocols. In the second project, B&VIs are supported to play golf. Golf flagsticks have sound marking devices with a buzzer, NodeMcu Lua ESP8266 ESP-12 WiFi board, and WiFi remote control. In the third project, an assistive device supports the orientation of B&VIs by measuring the distance to obstacles via Arduino Uno and HC-SR04. The distance is pronounced through headphones. In the fourth project, the soft-/hardware complex uses Raspberry Pi 3 B and Bytereal iBeacon fingerprinting to uniquely identify the B&VI location at industrial facilities.

A Deaf-Blind Man on the Job and at Home

1957 ◽  
Vol 51 (6) ◽  
pp. 255-257
Keyword(s):  
Daily Activities ◽  
Blind Person ◽  
Recent Letter ◽  
Blind Persons ◽  
At Home ◽  
Union College

Among the New Outlook's purposes is that of publishing, from, time to time, material indicating in a practical way how blind persons perform their professional jobs and other routines. In a recent letter to Miss Annette Dinsmore at AFB, reprinted below, Richard Kinney, of the staff of the Hddley Correspondence School, provides a sparkling recital of his work at that school as well as of his daily activities, which is suggestive of the versatility and resourcefulness that stand in such good stead for a blind person. There is an even far greater impact in Mr. Kinney's achievements and his irrepressible zest in the knowledge that he functions with a double handicap of deafness as well as blindness. Mr. Kinney graduated summa cum laude from Mt. Union College in 1954, and was valedictorian of his class.

scholarly journals In-home monitoring evaluation by home-dwelling older adults, caregivers and healthcare providers

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
B Pais ◽  
P Buluschek ◽  
T Nef ◽  
N Schütz ◽  
H Saner ◽  
...  
Keyword(s):  
Older Adults ◽  
Home Care ◽  
Older People ◽  
Healthcare Providers ◽  
Home Monitoring ◽  
Daily Activities ◽  
Healthcare Needs ◽  
Monitoring Technologies ◽  
The Impact ◽  
At Home

Abstract Background In Europe, population ageing is increasing the healthcare needs and costs. Both frailty and chronic diseases affecting older people reduce their ability to live independently. However, most older people prefer to age in their own homes. New development of in-home monitoring can play a role in staying independent, active and healthy. Our objective was to evaluate a new in-home monitoring system among home-dwelling older adults (OA), their family caregivers (FC), and their healthcare providers (HCP) for the support of home care. Methods The system continuously monitored OA’s daily activities (e.g., mobility, sleep habits, fridge visits, door events) at home by ambient sensor system (DomoCare®) and health-related events by wearable sensors (Fitbit®, ECG). In case of deviations in daily activities (e.g., changes in mobility), alerts were transmitted to HCP via email. Using specific questionnaires, the opinion of 13 OA, 13 FC, and 20 HCP were collected at the end of 12-month of follow-up focusing on their user experience and the impact of in-home monitoring on home care services. Results These preliminary results underlined that the majority of OA, FC, and HCP consider that in-home sensors can help staying at home, improving home care, reducing family stress, and preventing domestic accidents. The opinion tended to be more favourable toward ambient sensors (80%) than toward Fitbit® (67%) and ECG (64%). On average, OA (80%) and FC (73%) tended to be more enthusiast than HCP (63%). Some barriers reported by HCP were a fear of weakening of the relationship with OA and an excessive surveillance. Conclusions Overall, the opinion of OA, FC and HCP were positive related to in-home sensors, with HCP being more mixed about their use in clinical practice. Key messages In-home monitoring technologies seem to be generally well accepted. In-home monitoring technologies could be help facilitating home care of older people.

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