A Survey on Recent Advances in Wearable Fall Detection Systems
المؤلفون المشاركون
Ramachandran, Anita
Karuppiah, Anupama
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-17، 17ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-01-13
دولة النشر
مصر
عدد الصفحات
17
التخصصات الرئيسية
الملخص EN
With advances in medicine and healthcare systems, the average life expectancy of human beings has increased to more than 80 yrs.
As a result, the demographic old-age dependency ratio (people aged 65 or above relative to those aged 15–64) is expected to increase, by 2060, from ∼28% to ∼50% in the European Union and from ∼33% to ∼45% in Asia (Ageing Report European Economy, 2015).
Therefore, the percentage of people who need additional care is also expected to increase.
For instance, per studies conducted by the National Program for Health Care of the Elderly (NPHCE), elderly population in India will increase to 12% of the national population by 2025 with 8%–10% requiring utmost care.
Geriatric healthcare has gained a lot of prominence in recent years, with specific focus on fall detection systems (FDSs) because of their impact on public lives.
According to a World Health Organization report, the frequency of falls increases with increase in age and frailty.
Older people living in nursing homes fall more often than those living in the community and 40% of them experience recurrent falls (World Health Organization, 2007).
Machine learning (ML) has found its application in geriatric healthcare systems, especially in FDSs.
In this paper, we examine the requirements of a typical FDS.
Then we present a survey of the recent work in the area of fall detection systems, with focus on the application of machine learning.
We also analyze the challenges in FDS systems based on the literature survey.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ramachandran, Anita& Karuppiah, Anupama. 2020. A Survey on Recent Advances in Wearable Fall Detection Systems. BioMed Research International،Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1132382
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ramachandran, Anita& Karuppiah, Anupama. A Survey on Recent Advances in Wearable Fall Detection Systems. BioMed Research International No. 2020 (2020), pp.1-17.
https://search.emarefa.net/detail/BIM-1132382
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ramachandran, Anita& Karuppiah, Anupama. A Survey on Recent Advances in Wearable Fall Detection Systems. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1132382
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1132382
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر