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
File | Size |
---|---|
S1_Dataset/d1p50F | 248.3 KB |
S1_Dataset/d1p53F | 246.5 KB |
S1_Dataset/d1p45M | 179.1 KB |
S1_Dataset/d1p44M | 169.5 KB |
S1_Dataset/d1p51F | 164.5 KB |
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset activity_recognition_with_healthy_older_people_using_a_batteryless_wearable_sensor = fetch_ucirepo(id=427) # data (as pandas dataframes) X = activity_recognition_with_healthy_older_people_using_a_batteryless_wearable_sensor.data.features y = activity_recognition_with_healthy_older_people_using_a_batteryless_wearable_sensor.data.targets # metadata print(activity_recognition_with_healthy_older_people_using_a_batteryless_wearable_sensor.metadata) # variable information print(activity_recognition_with_healthy_older_people_using_a_batteryless_wearable_sensor.variables)
Torres, R., Visvanathan, R., & Ranasinghe, D. (2013). Activity recognition with healthy older people using a batteryless wearable sensor [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5GG6B.
Creators
Roberto Torres
Renuka Visvanathan
Damith Ranasinghe
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.