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Simulated Falls and Daily Living Activities Data Set Data Set
Download: Data Folder, Data Set Description

Abstract: 20 falls and 16 daily living activities were performed by 17 volunteers with 5 repetitions while wearing 6 sensors (3.060 instances) that attached to their head, chest, waist, wrist, thigh and ankle.

Data Set Characteristics:  

Time-Series

Number of Instances:

3060

Area:

Life

Attribute Characteristics:

Integer

Number of Attributes:

138

Date Donated

2018-06-06

Associated Tasks:

Classification

Missing Values?

Yes

Number of Web Hits:

10006


Source:

Ahmet Turan Özdemir
Phone: +90 352 207 6666 (int 32233)
Addr: Erciyes University, Electrical and Electronic Department, TR 38039, Melikgazi/Kayseri/Turkey
aturan '@' erciyes.edu.tr
www.aturan.com

Billur Barshan
Phone: +90 312 290 2161
Addr: Bilkent University, Electrical and Electronic Department, TR 06800, Bilkent/Ankara/Turkey
http://kilyos.ee.bilkent.edu.tr/~billur/
billur '@' ee.bilkent.edu.tr


Data Set Information:

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Attribute Information:

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Relevant Papers:

[1] Özdemir, A.T.; Barshan, B. “Detecting Falls with Wearable Sensors Using Machine Learning Techniques.”, Sensors 2014, 14, 10691-10708.
[2] Özdemir A.T., Orman A., ' Developing an iPhone smartphone based fall detection algorithm.', IEEE, 23rd Signal Processing and Communications Applications Conference (SIU), Malatya, Turkey, 16-19 May 2015, pp.1-4.
[3] Özdemir A.T., 'An Analysis on Sensor Locations of the Human Body for Wearable Fall Detection Devices: Principles and Practice.', Sensors 2016, 16, 11691.
[4] Ntanasis P., Pippa E., Özdemir A.T., Barshan B., Megalooikonomou V., 'Investigation of sensor placement for accurate fall detection', 6th EAI International Conference on Wireless Mobile Communication and Healthcare (MobiHealth), Milan, Italy, 14-16 Nov. 2016, pp.1-6



Citation Request:

Özdemir, A.T.; Barshan, B. “Detecting Falls with Wearable Sensors Using Machine Learning Techniques.”, Sensors 2014, 14, 10691-10708.


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