{"id":17202679,"url":"https://github.com/deepcharles/gait-data","last_synced_at":"2025-06-15T10:34:44.100Z","repository":{"id":66213250,"uuid":"184640478","full_name":"deepcharles/gait-data","owner":"deepcharles","description":"Data sets of gait time series","archived":false,"fork":false,"pushed_at":"2020-04-25T16:07:56.000Z","size":8,"stargazers_count":9,"open_issues_count":1,"forks_count":1,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-04-13T21:11:45.777Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/deepcharles.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2019-05-02T19:35:33.000Z","updated_at":"2025-03-03T13:27:26.000Z","dependencies_parsed_at":"2023-02-21T23:15:18.269Z","dependency_job_id":null,"html_url":"https://github.com/deepcharles/gait-data","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/deepcharles/gait-data","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Fgait-data","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Fgait-data/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Fgait-data/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Fgait-data/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/deepcharles","download_url":"https://codeload.github.com/deepcharles/gait-data/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Fgait-data/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":259960568,"owners_count":22938090,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-15T02:15:27.010Z","updated_at":"2025-06-15T10:34:44.093Z","avatar_url":"https://github.com/deepcharles.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data sets for the study of human locomotion with inertial measurements units\n\n\nThe data provided in this repository are described in the following article:\n- Truong, C., Barrois-Müller, R., Moreau, T., Provost, C., Vienne-Jumeau, A., Moreau, A., Vidal, P.-P., Vayatis, N., Buffat, S., Yelnik, A., Ricard, D., \u0026 Oudre, L. (2019). A data set for the study of human locomotion with inertial measurements units. Image Processing On Line (IPOL), 9. [[abstract]](https://deepcharles.github.io/publication/ipol-data-2019) [[doi]](https://doi.org/10.5201/ipol.2019.265) [[pdf]](http://deepcharles.github.io/files/ipol-walk-data-2019.pdf) [[online demo]](http://ipolcore.ipol.im/demo/clientApp/demo.html?id=265)\n\n\nPlease cite this article whenever you want to make a reference to this data set.\n\n\nA simple online exploration tool is available [online](http://ipolcore.ipol.im/demo/clientApp/demo.html?id=77777000084).\nData can be downloaded as a zipped archive (GaitData.zip, ~200MB):\n- [link 1](https://mycore.core-cloud.net/index.php/s/sTk4Vq8N3zefvKH/download)\n- [link 2](http://dev.ipol.im/~truong/GaitData.zip)\n\nOnce extracted, the data can be read using the following code snippets (in Python, R). Be sure to execute those lines while in the same directory as the extracted `GaitData` folder.\n\n#### Python\n\nSignals are loaded into [Pandas](https://pandas.pydata.org/) data frames. Please be sure to have it installed (`pip install pandas`).\n\n```python\nfrom load_data import get_code_list, load_trial, load_metadata\n\n\n# Load and manipulate all signals and metadata.\nall_codes = get_code_list()\nprint(\"There are {} trials.\".format(len(all_codes)))\nfor code in all_codes:\n    signal = load_trial(code)  # pandas data frame\n    metadata = load_metadata(code)  # dictionary\n    # Do something.\n    # ...\n```\n\n#### R\n\nBe sure to set the working directory (with the function `setwd`) to wherever the data file has been unzipped. To read JSON files, the package `jsonlite` must be installed.\n\n```R\nlibrary(\"jsonlite\")\ncode_list \u003c- fromJSON(\"code_list.json\")\n\nfor(code in code_list){\n    signal \u003c- read.csv(paste(code, \".csv\", sep=\"\"))\n    metadata \u003c- fromJSON(paste(code, \".json\", sep=\"\"))\n    # Do something.\n    # ...\n}\n\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeepcharles%2Fgait-data","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdeepcharles%2Fgait-data","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeepcharles%2Fgait-data/lists"}