کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5032811 1471135 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Review of fall detection techniques: A data availability perspective
ترجمه فارسی عنوان
بررسی تکنیک های شناسایی سقوط: دیدگاه دسترسی به داده ها
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی پزشکی
چکیده انگلیسی


- Review of fall detection techniques from the perspective of availability of fall data.
- Proposed a taxonomy to study fall detection that is independent of the type of sensors used and specific feature extraction/selection methods.
- Identified the approach of treating a fall as an abnormal activity as a plausible research direction.

A fall is an abnormal activity that occurs rarely; however, missing to identify falls can have serious health and safety implications on an individual. Due to the rarity of occurrence of falls, there may be insufficient or no training data available for them. Therefore, standard supervised machine learning methods may not be directly applied to handle this problem. In this paper, we present a taxonomy for the study of fall detection from the perspective of availability of fall data. The proposed taxonomy is independent of the type of sensors used and specific feature extraction/selection methods. The taxonomy identifies different categories of classification methods for the study of fall detection based on the availability of their data during training the classifiers. Then, we present a comprehensive literature review within those categories and identify the approach of treating a fall as an abnormal activity to be a plausible research direction. We conclude our paper by discussing several open research problems in the field and pointers for future research.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Medical Engineering & Physics - Volume 39, January 2017, Pages 12-22
نویسندگان
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