{
  "abstract": "Reliable cardiac monitoring in daily work environments could support applications such as stress assessment and mental workload tracking. Radar sensing provides a promising contactless solution by capturing subtle chest motion without requiring wearable devices. However, many existing methods assume quasi-static conditions and experience substantial performance degradation in office environments because of self-induced interference, including body motion and the often-overlooked effect of irregular respiration. To address these challenges, we analyze the temporal structure of cardiac mechanical activity and identify two key properties: short-duration impulsiveness and short-term quasi-periodicity. Guided by these properties, we propose a signal-processing paradigm for reliable cardiac sensing under dynamic interference. Specifically, we design a bidirectional wavelet transform to extract pulse-like cardiac events from complex radar signals, a periodicity-guided multi-scale fusion strategy to retain rhythmically consistent components, and an adaptive spatial selection method to identify reliable chest reflections. We implement this paradigm as a real-time prototype system, DailyBeat, using a commercial mmWave radar. Experiments across multiple participants and office activities demonstrate that DailyBeat recovers detailed cardiac mechanical waveforms and accurately estimates heart rate, inter-beat intervals, and a QT-related mechanical surrogate, enabling fine-grained and unobtrusive cardiac monitoring in daily office environments",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "name": "Zhaoxin Chang"
    },
    {
      "name": "Pei Wang"
    },
    {
      "name": "Xujun Ma"
    },
    {
      "name": "Luan Chen"
    },
    {
      "name": "Fusang Zhang"
    },
    {
      "name": "Duo Zhang"
    },
    {
      "name": "Badii Jouaber"
    },
    {
      "name": "Daqing Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8c906d8fms9hp.bib",
  "cited_by": 0,
  "doi": "10.1145/3831967",
  "fulltext_url": null,
  "id": "8c906d8fms9hp",
  "issns": [
    "2474-9567"
  ],
  "landing_url": "https://hal.science/hal-05773505v1",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
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  "pdf_url": "https://hal.science/hal-05773505/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-30",
  "publisher": "ACM",
  "ris": "https://research.draconitic.com/paper/8c906d8fms9hp.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:45Z",
      "native_id": "hal-05773505",
      "source": "hal",
      "url": "https://hal.science/hal-05773505v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "hal:1.sdv.ib",
      "subfield": "systems-synthetic"
    },
    {
      "field": "medicine",
      "origin": "hal:2.sdv.mhep.csc",
      "subfield": "cardiovascular"
    }
  ],
  "title": "DailyBeat: reliable cardiac sensing under self-induced dynamic interference using mmWave radar",
  "title_text": "DailyBeat: reliable cardiac sensing under self-induced dynamic interference using mmWave radar",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:45Z",
  "url": "https://research.draconitic.com/paper/8c906d8fms9hp",
  "venue": "Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies",
  "versions": []
}