Python general purpose human motion inertial data processing package.
Project description
Scikit Digital Health (SKDH) is a Python package with methods for ingesting and analyzing wearable inertial sensor data.
Documentation: https://scikit-digital-health.readthedocs.io/en/latest/
Bug reports: https://github.com/PfizerRD/scikit-digital-health/issues
Contributing: https://scikit-digital-health.readthedocs.io/en/latest/src/dev/contributing.html
SKDH provides the following:
Methods for ingesting data from binary file formats (ie Axivity, GeneActiv)
Preprocessing of accelerometer data
Common time-series signal features
Common time-series/inertial data analysis functions
Inertial data analysis algorithms (ie gait, sit-to-stand, sleep, activity)
Availability
SKDH is available on both conda-forge and PyPI.
conda install scikit-digital-health -c conda-forge
or
pip install scikit-digital-health
Build Requirements
As of 0.9.15, Scikit Digital Health is built using Meson.
Citation
If you use SKDH in your research, please include the following citation:
Adamowicz, Y. Christakis, M. D. Czech, and T. Adamusiak, “SciKit Digital Health: Python Package for Streamlined Wearable Inertial Sensor Data Processing,” JMIR mHealth and uHealth, vol. 10, no. 4, p. e36762, Apr. 2022, doi: 10.2196/36762.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distributions
Hashes for scikit_digital_health-0.15.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6f6742e5dd1aed096559fb691347cdb8fa0736da41c60c39624682b614ae6396 |
|
MD5 | 6917e2e5a588b345413585d6801f15e6 |
|
BLAKE2b-256 | a2837c0291d5eb7291c9e406cbe2cf08beb0eac2c8e6673df39dde4871455507 |
Hashes for scikit_digital_health-0.15.0-cp312-cp312-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 371f394c0b26c7b0b2d4a4b135a34137af9501a96a1dd5554ff5feff18f225e8 |
|
MD5 | 8c2dac5680e9303ea38b78cfe11b79b0 |
|
BLAKE2b-256 | 86ff7054ef12e35caa0a87f05f57bed02e587dd1e51d387dcf1fd07919cc8fcc |
Hashes for scikit_digital_health-0.15.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | db2ee4203fcb0398639da1c61d003d6fac4eb5450b642ec2611f9c5f6565c912 |
|
MD5 | 2972a8f21bc6dd5f3523eb3a2b21c024 |
|
BLAKE2b-256 | 71f019043e7064292be73f031876617fdf53aff5812dce94c769150585161665 |
Hashes for scikit_digital_health-0.15.0-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8e018b419a746327f977936a233740b9427efb0b04a788d41c08d45b240a6e8e |
|
MD5 | 7649f1d4f75fbb1596ccae8f1f3e2d88 |
|
BLAKE2b-256 | e5e72898e7d39541df550a3a4cd259cbf7ce4c751a53590dd5f143419ffd117d |
Hashes for scikit_digital_health-0.15.0-cp311-cp311-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 663d2199d7b11c74445f06b5655cefa1ab2204d1b9c9309b946416ac3f8ff03b |
|
MD5 | 3411a45b77284dff52e817e9d3ae26fb |
|
BLAKE2b-256 | c6681a5b36a77402e75c3eb1fc1dd0722f1e0af8ec2c967f9da19cce72aed229 |
Hashes for scikit_digital_health-0.15.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5a22d85cfb7df91d41c56299514c88358aa2793880e871d55a190c0012c07b55 |
|
MD5 | b93ae4d620f05c11046d1048230c52aa |
|
BLAKE2b-256 | 97d8d4fb490da91575d7cc29339de8e9b3678664da3bdade2a0803a347d14407 |
Hashes for scikit_digital_health-0.15.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d34e71f2f4522856be77d49a3dce71a2fd5a220a003b0d94fa73fbe989fe7ad5 |
|
MD5 | 1861af822230f416a576aa8baf19b636 |
|
BLAKE2b-256 | 0a103ce6499c1fe82b1a8481829e95614b6818a93dd90834ec7c24c7a9537d54 |
Hashes for scikit_digital_health-0.15.0-cp310-cp310-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6604f7d436cdc2fb2e7e3fabbe50b47cab67e3e31303ad77eff0457afd1c1e69 |
|
MD5 | 79046eb88b7f6db3ecbc4088994d5a96 |
|
BLAKE2b-256 | 5bd589bc2dfc6d41de01815b1bb5708a17c9f3a2e143f8c5caddd1bc2d7cf20d |
Hashes for scikit_digital_health-0.15.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 78e380c668f14f66ce6c5a9a3f2b6f8317fc9595e67085fe138a34e67acddc38 |
|
MD5 | cacc5f3f2de074bc0f0a425ddbf50e04 |
|
BLAKE2b-256 | 97d25e7b098d0f85ed2b9100eff71e9a3b09aff86c59beb9fb3539cc639d7cea |
Hashes for scikit_digital_health-0.15.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d66c3dc99e96bd60528c511cf02241f6f916682486ca4cdfedd809cfd68e98f7 |
|
MD5 | ad335bf017ad203bef9cead77738a64c |
|
BLAKE2b-256 | d83baf192ff4b5fddaa26c98282dbe92b9d0d2459c6e5187cfe98003147a633d |
Hashes for scikit_digital_health-0.15.0-cp39-cp39-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d0449c1286b45cc55a64b76c3c4810e825b40ff5a4e2925d835d52b66e63f58b |
|
MD5 | 154b6a5b1885ffec5015d1d3136233ec |
|
BLAKE2b-256 | 8879673339780b32ea5602f820b2b172860ff5f4a0d3a2e0bc8c1e412de56540 |
Hashes for scikit_digital_health-0.15.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | e57ad816d55ddca868582930fbe1d13d57876bb9fdddd42140876876cb71dacb |
|
MD5 | cb1dea026c9ec5130f24f9440d07ea75 |
|
BLAKE2b-256 | c7559e8b8b778ed1c16970dc3b5c9874e059693789e784b7abe21148f17f299b |
Hashes for scikit_digital_health-0.15.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 18cae02952ab8702d2306f7d51688ba0b11f99917173391609ff99bdaa1591ab |
|
MD5 | b351b3f06fc924e01484301d03f88479 |
|
BLAKE2b-256 | ab2d67825c59afe09010afa905ddec62358d553d4faf8ecc8ff54137828164e7 |
Hashes for scikit_digital_health-0.15.0-cp38-cp38-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 01664090a7bc5fd118b4b5de235d482ca3070489ce4c0a44f5eed7d6b698f6bb |
|
MD5 | 186f0b0b70a945e0f3b1188e7d7bc494 |
|
BLAKE2b-256 | 7bd8458a4a3e7c9ef5b7207da7d2a7b415a4ecec393de6b96850bed285511837 |
Hashes for scikit_digital_health-0.15.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 20d378548a523f246bd21581fcacd57dd330c0bad05c54d4aa38cc68e26598a6 |
|
MD5 | f11de8cfcb513a4ca3804ba4f3d24b38 |
|
BLAKE2b-256 | aaa1e96022ee21d4b1ae059037e6c4def1a5a6c59b27505dc8d799f826b1b0e8 |
Hashes for scikit_digital_health-0.15.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 06cf33a5f4319fdd352eaa62b7a8d5594d935876dd42b1fc3e0c5951951c4c68 |
|
MD5 | 6dc51da34ba45a43605f0bc2a541e8d8 |
|
BLAKE2b-256 | 5550cd374cfb87ef64939bb3ab0a31cbe7ad3ca75dcc4b825c744060da435448 |