Database Open Access
Long Term Movement Monitoring Database
Published: June 20, 2016. Version: 1.0.0
New Database Added: LTMM (June 20, 2016, midnight)
The Long Term Movement Monitoring database contains 3-day 3D accelerometer recordings of 71 elder community residents, used to study gait, stability, and fall risk.
Please include the standard citation for PhysioNet:
(show more options)
Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.
Abstract
The LTMM database contains 3-day 3D accelerometer recordings of 71 elder community residents, used to study gait, stability, and fall risk.
Subjects
Seventy-one community-living elder adults (mean age = 78.36 ± 4.71 years; range = 65-87 years) were studied. Subjects were included if they were not previously clinically diagnosed with any gait or balance disorders, and if they were cognitively intact, with a Mini-Mental State Examination score above 24 points. Subjects were classified as fallers and nonfallers based on their self-report of previous falls. If subjects had at least 2 falls in the past year, they were considered fallers, otherwise they were considered non-fallers.
Experimental Procedure
The subjects underwent multiple protocols and evaluations:
- Clinical and Traditional Fall Risk Assessment: Functional performance based assessments were performed in the laboratory including the Dynamic Gait Index (DGI), the Berg Balance Scale (BBS), the Timed Up and Go test (TUG), and the Four Square Step Test (FSST). The Mini Mental State Examination (MMSE) and the Activities-specific Balance Confidence scale (ABC) were also performed. The results of these afforementioned tests can be found from column 29 of the
ClinicalDemogData_COFL.xlsx
spreadsheet. - Gait assessment in the Lab: Participants walked for 1 minute at a comfortable, self-selected speed while wearing a gait belt. A 3D accelerometer was worn on the lower back to quantify gait using previously validated methods. The accelerometer files recordings of these tests can be found in the
LabWalks
directory in MIT format. - Three-day Activities of Daily Living Assessment: After performing tests in the laboratory, participants were asked to wear a 3D accelerometer on their lower back for 3 consecutive days (except during activities like showering or swimming). Subjects received a diary for tracking when and why they took off and put on the device, shown in the
ReportHome75h.xlsx
spreadsheet. These are the main recordings of this database and can be found in MIT format below.
Files
- General Information Files
- The
ClinicalDemogData_COFL.xlsx
spreadsheet contains information about the subjects such as their age, gender, and how many times they fell within the last year, and the results of the performed clinical tests. - The
ReportHome75h.xlsx
spreadsheet contains self-reported events by the subjects regarding when and why they put on and removed their accelerometers over their three day recordings.
- The
- High Resolution Accelerometer Recording Files
- The three day 3D accelerometer recordings are in standard MIT format, with each one containing a binary signal (
.dat
) file and a corresponding header (.hea
)file used to interpret the signals. The file names are in the form CO0NN for non-fallers or FO0NN for fallers, where NN is the subject number for that group. - The 1 minute lab walk recordings within the
LabWalks
directory are in the same format as the three day recordings described above. The file names are also in a similar form.
- The three day 3D accelerometer recordings are in standard MIT format, with each one containing a binary signal (
Access
Access Policy:
Anyone can access the files, as long as they conform to the terms of the specified license.
License (for files):
Open Data Commons Attribution License v1.0
Discovery
DOI (version 1.0.0):
https://doi.org/10.13026/C2S59C
Topics:
risk
stability
accelerometer
gait
Corresponding Author
Files
Total uncompressed size: 20.8 GB.
Access the files
- Download the ZIP file (20.8 GB)
- Access the files using the Google Cloud Storage Browser here. Login with a Google account is required.
-
Access the data using the Google Cloud command line tools (please refer to the gsutil
documentation for guidance):
gsutil -m -u YOUR_PROJECT_ID cp -r gs://ltmm-1.0.0.physionet.org DESTINATION
-
Download the files using your terminal:
wget -r -N -c -np https://physionet.org/files/ltmm/1.0.0/
-
Download the files using AWS command line tools:
aws s3 sync --no-sign-request s3://physionet-open/ltmm/1.0.0/ DESTINATION