RF Safe

Single access point localisation for wearable wireless sensors.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2008 · Unclear · Insufficient evidence

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UnclearInsufficient evidencePaper 2839

The paper develops a method to track a subject’s location using RF signals from wearable wireless sensors, combining RSSI and LQI from a single basestation. With suitable filtering, the authors report accuracy approaching that of a multiple-basestation locali…

Study snapshot

PublicationAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2008
Study typeengineering
Reported directionUnclear
Evidence ratingInsufficient

Abstract

Knowledge of a subject's location and motion throughout an environment is of significant use to in-home health monitoring and activity recognition systems. This work develops a method of tracking a subject's location using the radio frequency (RF) signals emanating from wearable wireless sensors. It differs from other RF location tracking work in that it utilises the hardware which would already be deployed in a biomedical monitoring application. This is achieved by combining the RSSI (Received Signal Strength Indicator) and LQI (Link Quality Indicator) readings from a single basestation. It is shown that accuracy approaching that of a multiple basestation localisation deployment is achievable by using a suitable level of filtering. As a result of this work, location information can be more readily and cheaply incorporated into future biomedical monitoring applications.

Machine Enhanced Logic

AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeengineering
Effect directionunclear
PopulationNot supplied
Sample sizeNot supplied
ExposureRF
Evidence strengthInsufficientConfidence: 74% · Peer reviewed: yes

Main findings

The paper develops a method to track a subject’s location using RF signals from wearable wireless sensors, combining RSSI and LQI from a single basestation. With suitable filtering, the authors report accuracy approaching that of a multiple-basestation localisation deployment.

Outcomes measured

  • Localization/tracking accuracy using RF signals (RSSI, LQI) from wearable sensors
  • Feasibility of single basestation localisation with filtering

Limitations

  • No frequency, power, or SAR/exposure level details provided in the abstract
  • No sample size, participant characteristics, or study setting details provided in the abstract
  • No quantitative accuracy metrics or error statistics reported in the abstract
View raw extracted JSON
{
  "study_type": "engineering",
  "exposure": {
    "band": "RF",
    "source": "wearable wireless sensors",
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": null
  },
  "population": null,
  "sample_size": null,
  "outcomes": [
    "Localization/tracking accuracy using RF signals (RSSI, LQI) from wearable sensors",
    "Feasibility of single basestation localisation with filtering"
  ],
  "main_findings": "The paper develops a method to track a subject’s location using RF signals from wearable wireless sensors, combining RSSI and LQI from a single basestation. With suitable filtering, the authors report accuracy approaching that of a multiple-basestation localisation deployment.",
  "effect_direction": "unclear",
  "limitations": [
    "No frequency, power, or SAR/exposure level details provided in the abstract",
    "No sample size, participant characteristics, or study setting details provided in the abstract",
    "No quantitative accuracy metrics or error statistics reported in the abstract"
  ],
  "evidence_strength": "insufficient",
  "confidence": 0.74,
  "peer_reviewed_likely": "yes",
  "keywords": [
    "wearable wireless sensors",
    "radio frequency",
    "localisation",
    "tracking",
    "RSSI",
    "LQI",
    "single basestation",
    "filtering",
    "in-home health monitoring"
  ],
  "suggested_hubs": []
}
AI can be wrong. Always verify against the paper.

AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1109/iembs.2008.4650197
PubMed: 19163700

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