{"id":17202678,"url":"https://github.com/deepcharles/fall-data","last_synced_at":"2026-02-16T02:01:53.335Z","repository":{"id":66213259,"uuid":"431869553","full_name":"deepcharles/fall-data","owner":"deepcharles","description":"A data set for fall detection with smart floor sensors","archived":false,"fork":false,"pushed_at":"2022-10-07T14:47:03.000Z","size":156,"stargazers_count":3,"open_issues_count":0,"forks_count":1,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-07-27T21:45:03.395Z","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":"2021-11-25T14:13:24.000Z","updated_at":"2024-07-07T22:31:54.000Z","dependencies_parsed_at":null,"dependency_job_id":"868a1fa7-dd44-418f-a854-831f58b08b40","html_url":"https://github.com/deepcharles/fall-data","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/deepcharles/fall-data","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Ffall-data","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Ffall-data/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Ffall-data/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Ffall-data/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/deepcharles","download_url":"https://codeload.github.com/deepcharles/fall-data/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepcharles%2Ffall-data/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29498348,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-16T01:48:08.113Z","status":"online","status_checked_at":"2026-02-16T02:00:08.638Z","response_time":115,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":"2024-10-15T02:15:26.992Z","updated_at":"2026-02-16T02:01:53.329Z","avatar_url":"https://github.com/deepcharles.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# A data set for fall detection with smart floor sensors\n\nData can be downloaded as a zipped archive (FallData.tar.gz, ~330MB):\n- [link 1](https://plmbox.math.cnrs.fr/f/a05ad8fbe7674392962b/?dl=1)\n\nAlternatively, running in a terminal\n\n\u003e python download_data.py\n\nautomatically downloads and extracts the data. This code requires Python 3 and `tqdm` (`pip install tqdm`).\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 `FallData` folder.\n\n#### Python\n\nSignals are loaded into Numpy arrays. Please be sure to have it installed (`pip install numpy`), as well as `tqdm` (`pip install tqdm`).\n\n```python\nfrom load_data import get_code_list, load_signal, 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_signal(code)  # numpy array (n_samples, n_dims)\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    if (startsWith(code, \"u-\")){\n        filename \u003c- paste(\"FallData/Unconstrained/\", code, sep=\"\")\n    }\n    if (startsWith(code, \"c-\")){\n        filename \u003c- paste(\"FallData/Controlled/\", code, sep=\"\")\n    }\n    if (startsWith(code, \"cnf-\")){\n        filename \u003c- paste(\"FallData/ControlledNoFall/\", code, sep=\"\")\n    }\n    signal \u003c- read.csv(paste(filename, \".csv\", sep=\"\"))\n    metadata \u003c- fromJSON(paste(filename, \".json\", sep=\"\"))\n    # Do something.\n    # ...\n}\n\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeepcharles%2Ffall-data","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdeepcharles%2Ffall-data","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeepcharles%2Ffall-data/lists"}