Real Time Processing and Transferring ECG Signal by a Mobile Phone.

PAPER pubmed Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH 2014 Engineering / measurement Effect: unclear Evidence: Insufficient

Read original paper → DOI: 10.5455/aim.2014.22.389-392 PMID: 25684847 Evidence Lab

Abstract

The real-time ECG signal processing system based on mobile phones is very effective in identifying continuous ambulatory patients. It could monitor cardiovascular patients in their daily life and warns them in case of cardiac arrhythmia. An ECG signal of a patient is processed by a mobile phone with this proposed algorithm. An IIR low-pass filter is used to remove the noise and it has the 55 Hz cutoff frequency and order 3. The obtained SNR showed a desirable noise removal and it helps physicians in their diagnosis. In this paper, Hilbert transform was used and the R peaks are important component to differ normal beats from abnormal ones. The results of sensitivity and positive predictivity of algorithm are 96.97% and 95.63% respectively. If an arrhythmia occurred, 4 seconds of this signal is displayed on the mobile phone then it will be sent to a remote medical center by TCP/IP protocol.

AI evidence extraction

At a glance

Study type

Engineering / measurement

Effect direction

unclear

Population

cardiovascular patients / ambulatory patients (as described)

Sample size

—

Exposure

mobile phone

Evidence strength

Insufficient

Confidence: 74% · Peer-reviewed: yes

Main findings

A mobile-phone-based real-time ECG processing system is described using an IIR low-pass filter (55 Hz cutoff, order 3) and Hilbert transform for R-peak detection. Reported algorithm performance was 96.97% sensitivity and 95.63% positive predictivity, and when arrhythmia occurs a 4-second ECG segment is displayed and sent to a remote medical center via TCP/IP.

Outcomes measured

ECG signal processing performance (SNR improvement/noise removal)
Arrhythmia detection algorithm sensitivity
Arrhythmia detection algorithm positive predictivity
Remote transmission of ECG segment via TCP/IP

Limitations

No EMF/RF exposure metrics (frequency, power, SAR) are reported
No sample size or participant characteristics are provided in the abstract
No health effects of EMF exposure are assessed; focus is on signal processing/telemedicine performance

View raw extracted JSON

{
    "study_type": "engineering",
    "exposure": {
        "band": null,
        "source": "mobile phone",
        "frequency_mhz": null,
        "sar_wkg": null,
        "duration": null
    },
    "population": "cardiovascular patients / ambulatory patients (as described)",
    "sample_size": null,
    "outcomes": [
        "ECG signal processing performance (SNR improvement/noise removal)",
        "Arrhythmia detection algorithm sensitivity",
        "Arrhythmia detection algorithm positive predictivity",
        "Remote transmission of ECG segment via TCP/IP"
    ],
    "main_findings": "A mobile-phone-based real-time ECG processing system is described using an IIR low-pass filter (55 Hz cutoff, order 3) and Hilbert transform for R-peak detection. Reported algorithm performance was 96.97% sensitivity and 95.63% positive predictivity, and when arrhythmia occurs a 4-second ECG segment is displayed and sent to a remote medical center via TCP/IP.",
    "effect_direction": "unclear",
    "limitations": [
        "No EMF/RF exposure metrics (frequency, power, SAR) are reported",
        "No sample size or participant characteristics are provided in the abstract",
        "No health effects of EMF exposure are assessed; focus is on signal processing/telemedicine performance"
    ],
    "evidence_strength": "insufficient",
    "confidence": 0.7399999999999999911182158029987476766109466552734375,
    "peer_reviewed_likely": "yes",
    "keywords": [
        "ECG",
        "mobile phone",
        "real-time processing",
        "IIR low-pass filter",
        "Hilbert transform",
        "R-peak detection",
        "arrhythmia detection",
        "telemedicine",
        "TCP/IP"
    ],
    "suggested_hubs": []
}

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

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