Literature DB >> 33503949

Self-Organizing IoT Device-Based Smart Diagnosing Assistance System for Activities of Daily Living.

Yu Jin Park1, Seol Young Jung2, Tae Yong Son1, Soon Ju Kang2.   

Abstract

Activity of daily living (ADL) is a criterion for evaluating the performance ability of daily life by recognizing various activity events occurring in real life. However, most of the data necessary for ADL evaluation are collected only through observation and questionnaire by the patient or the patient's caregiver. Recently, Internet of Things(IoT) device studies using various environmental sensors are being used for ADL collection and analysis. In this paper, we propose an IoT Device Platform for ADL capability measurement. Wearable devices and stationary devices recognize activity events in real environments and perform user identification through various sensors. The user's ADL data are sent to the network hub for analysis. The proposed IoT platform devices support many sensor devices such as acceleration, flame, temperature, and humidity in order to recognize various activities in real life. In addition, in this paper, using the implemented platform, ADL measurement test was performed on hospital patients. Through this test, the accuracy and reliability of the platform are analyzed.

Entities:  

Keywords:  IoT device; activity of daily living; home healthcare

Mesh:

Year:  2021        PMID: 33503949      PMCID: PMC7866208          DOI: 10.3390/s21030785

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  23 in total

Review 1.  Gait dynamics in Parkinson's disease: common and distinct behavior among stride length, gait variability, and fractal-like scaling.

Authors:  Jeffrey M Hausdorff
Journal:  Chaos       Date:  2009-06       Impact factor: 3.642

Review 2.  The Elderly's Independent Living in Smart Homes: A Characterization of Activities and Sensing Infrastructure Survey to Facilitate Services Development.

Authors:  Qin Ni; Ana Belén García Hernando; Iván Pau de la Cruz
Journal:  Sensors (Basel)       Date:  2015-05-14       Impact factor: 3.576

3.  A survey on ambient-assisted living tools for older adults.

Authors:  Parisa Rashidi; Alex Mihailidis
Journal:  IEEE J Biomed Health Inform       Date:  2013-05       Impact factor: 5.772

Review 4.  Assessment of Activities of Daily Living, Self-Care, and Independence.

Authors:  Michelle E Mlinac; Michelle C Feng
Journal:  Arch Clin Neuropsychol       Date:  2016-07-29       Impact factor: 2.813

5.  Cognitive and motor impairments predict functional declines in patients with vascular dementia.

Authors:  Patricia A Boyle; Ronald A Cohen; Robert Paul; David Moser; Norman Gordon
Journal:  Int J Geriatr Psychiatry       Date:  2002-02       Impact factor: 3.485

6.  An automatic non-invasive method for Parkinson's disease classification.

Authors:  Deepak Joshi; Aayushi Khajuria; Pradeep Joshi
Journal:  Comput Methods Programs Biomed       Date:  2017-04-18       Impact factor: 5.428

7.  Visual sensor based abnormal event detection with moving shadow removal in home healthcare applications.

Authors:  Young-Sook Lee; Wan-Young Chung
Journal:  Sensors (Basel)       Date:  2012-01-05       Impact factor: 3.576

Review 8.  The tool in the brain: apraxia in ADL. Behavioral and neurological correlates of apraxia in daily living.

Authors:  Marta M N Bieńkiewicz; Marie-Luise Brandi; Georg Goldenberg; Charmayne M L Hughes; Joachim Hermsdörfer
Journal:  Front Psychol       Date:  2014-04-23

9.  Noncontact Sleep Study by Multi-Modal Sensor Fusion.

Authors:  Ku-Young Chung; Kwangsub Song; Kangsoo Shin; Jinho Sohn; Seok Hyun Cho; Joon-Hyuk Chang
Journal:  Sensors (Basel)       Date:  2017-07-21       Impact factor: 3.576

10.  A 52 month follow-up of functional decline in nursing home residents - degree of dementia contributes.

Authors:  Anne-Sofie Helvik; Knut Engedal; Jūratė Saltytė Benth; Geir Selbæk
Journal:  BMC Geriatr       Date:  2014-04-10       Impact factor: 3.921

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.