Book section Open Access

Monitoring activities of daily living using audio analysis and a RaspberryPI: A use case on bathroom activity monitoring

Siantikos, Georgios; Giannakopoulos, Theodoros; Konstantopoulos, Stasinos


JSON Export

{
  "files": [
    {
      "links": {
        "self": "https://zenodo.org/api/files/fdd18440-0f5b-465e-b2b7-b7e6ac221598/siantikos-etal-2017.pdf"
      }, 
      "checksum": "md5:05d215a318805a531ef2891774666106", 
      "bucket": "fdd18440-0f5b-465e-b2b7-b7e6ac221598", 
      "key": "siantikos-etal-2017.pdf", 
      "type": "pdf", 
      "size": 1110964
    }
  ], 
  "owners": [
    20955
  ], 
  "doi": "10.1007/978-3-319-62704-5_2", 
  "stats": {
    "version_unique_downloads": 23.0, 
    "unique_views": 47.0, 
    "views": 57.0, 
    "downloads": 27.0, 
    "unique_downloads": 23.0, 
    "version_unique_views": 47.0, 
    "volume": 29996028.0, 
    "version_downloads": 27.0, 
    "version_views": 57.0, 
    "version_volume": 29996028.0
  }, 
  "links": {
    "doi": "https://doi.org/10.1007/978-3-319-62704-5_2", 
    "latest_html": "https://zenodo.org/record/835854", 
    "bucket": "https://zenodo.org/api/files/fdd18440-0f5b-465e-b2b7-b7e6ac221598", 
    "badge": "https://zenodo.org/badge/doi/10.1007/978-3-319-62704-5_2.svg", 
    "html": "https://zenodo.org/record/835854", 
    "latest": "https://zenodo.org/api/records/835854"
  }, 
  "created": "2017-07-28T15:56:01.329194+00:00", 
  "updated": "2019-04-10T04:17:09.303656+00:00", 
  "conceptrecid": "835853", 
  "revision": 5, 
  "id": 835854, 
  "metadata": {
    "access_right_category": "success", 
    "part_of": {
      "title": "Revised Selected Papers of the 2nd Second International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2016). Communications in Computer and Information Science, vol. 736"
    }, 
    "doi": "10.1007/978-3-319-62704-5_2", 
    "description": "<p>A framework that utilizes audio information for recognition of activities of daily living (ADLs) in the context of a health monitoring environment is presented in this chapter. We propose integrating a Raspberry PI single-board PC that is used both as an audio acquisition and analysis unit. So Raspberry PI captures audio samples from the attached microphone device and executes a set of real-time feature extraction and classification procedures, in order to provide continuous and online audio event recognition to the end user.<br>\nFurthermore, a practical workflow is presented, that helps the technicians that setup the device to perform a fast, user-friendly and robust tuning and calibration procedure. As a result, the technician is capable of \"training\"' the device without any need for prior knowledge of machine learning techniques. The proposed system has been evaluated against a particular scenario that is rather important in the context of any healthcare monitoring system for the elder: In particular, we have focused on the \"bathroom scenario\" according to which, a Raspberry PI device equipped with a single microphone is used to monitor bathroom activity on a 24/7 basis in a privacy-aware manner, since no audio data is stored or transmitted. The presented experimental results prove that the proposed framework can be successfully used for audio event recognition tasks.</p>", 
    "license": {
      "id": "other-at"
    }, 
    "title": "Monitoring activities of daily living using audio analysis and a RaspberryPI: A use case on bathroom activity monitoring", 
    "relations": {
      "version": [
        {
          "count": 1, 
          "index": 0, 
          "parent": {
            "pid_type": "recid", 
            "pid_value": "835853"
          }, 
          "is_last": true, 
          "last_child": {
            "pid_type": "recid", 
            "pid_value": "835854"
          }
        }
      ]
    }, 
    "imprint": {
      "publisher": "Springer", 
      "place": "Germany"
    }, 
    "communities": [
      {
        "id": "radio"
      }, 
      {
        "id": "roboskel"
      }
    ], 
    "grants": [
      {
        "code": "643892", 
        "links": {
          "self": "https://zenodo.org/api/grants/10.13039/501100000780::643892"
        }, 
        "title": "Robots in assisted living environments: Unobtrusive, efficient, reliable and modular solutions for independent ageing", 
        "acronym": "RADIO", 
        "program": "H2020", 
        "funder": {
          "doi": "10.13039/501100000780", 
          "acronyms": [
            "EC"
          ], 
          "name": "European Commission", 
          "links": {
            "self": "https://zenodo.org/api/funders/10.13039/501100000780"
          }
        }
      }
    ], 
    "keywords": [
      "audio analysis", 
      "activities of daily living", 
      "health monitoring", 
      "remote monitoring", 
      "audio event recognition"
    ], 
    "publication_date": "2017-07-20", 
    "creators": [
      {
        "affiliation": "NCSR \"Demokritos\"", 
        "name": "Siantikos, Georgios"
      }, 
      {
        "affiliation": "NCSR \"Demokritos\"", 
        "name": "Giannakopoulos, Theodoros"
      }, 
      {
        "affiliation": "NCSR \"Demokritos\"", 
        "name": "Konstantopoulos, Stasinos"
      }
    ], 
    "access_right": "open", 
    "resource_type": {
      "subtype": "section", 
      "type": "publication", 
      "title": "Book section"
    }, 
    "related_identifiers": [
      {
        "scheme": "url", 
        "relation": "isIdenticalTo", 
        "identifier": "https://link.springer.com/chapter/10.1007%2F978-3-319-62704-5_2"
      }, 
      {
        "scheme": "url", 
        "relation": "isIdenticalTo", 
        "identifier": "https://www.researchgate.net/publication/318550233"
      }
    ]
  }
}
57
27
views
downloads
Views 57
Downloads 27
Data volume 30.0 MB
Unique views 47
Unique downloads 23

Share

Cite as