Activity recognition with healthy older people using a batteryless wearable sensor

Donated on 12/11/2016

Sequential motion data from 14 healthy older people aged 66 to 86 years old using a batteryless, wearable sensor on top of their clothing for the recognition of activities in clinical environments.

Dataset Characteristics

Sequential

Subject Area

Health and Medicine

Associated Tasks

Classification

Feature Type

Real

# Instances

75128

# Features

9

Dataset Information

Additional Information

This dataset contains the motion data of 14 healthy older aged between 66 and 86 years old, performed broadly scripted activities using a batteryless, wearable sensor on top of their clothing at sternum level. Data is sparse and noisy due to the use of a passive sensor. Participants were allocated in two clinical room settings (S1 and S2). The setting of S1 (Room1) uses 4 RFID reader antennas around the room (one on ceiling level, and 3 on wall level) for the collection of data, whereas the room setting S2 (Room2) uses 3 RFID reader antennas (two at ceiling level and one at wall level) for the collection of motion data. The activities performed were: walking to the chair, sitting on the chair, getting off the chair, walking to bed, lying on bed, getting off the bed and walking to the door. Hence the possible class labels assigned for every sensor observation are: - Sitting on bed - Sitting on chair - Lying on bed - Ambulating, where ambulating includes standing, walking around the room.

Has Missing Values?

No

Variable Information

The content of the file is as follows: Comma separated values (CSV) format. Column 1: Time in seconds Column 2: Acceleration reading in G for frontal axis Column 3: Acceleration reading in G for vertical axis Column 4: Acceleration reading in G for lateral axis Column 5: Id of antenna reading sensor Column 6: Received signal strength indicator (RSSI) Column 7: Phase Column 8: Frequency Column 9: Label of activity, 1: sit on bed, 2: sit on chair, 3: lying, 4: ambulating In addition, gender of participant is included in the last character of file name eg: d1p33F (F:female).

Dataset Files

FileSize
S1_Dataset/d1p50F248.3 KB
S1_Dataset/d1p53F246.5 KB
S1_Dataset/d1p45M179.1 KB
S1_Dataset/d1p44M169.5 KB
S1_Dataset/d1p51F164.5 KB

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Creators

Roberto Torres

Renuka Visvanathan

Damith Ranasinghe

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