Radar human breathing dataset for applications of ambient assisted living and search and rescue operations

Cansu Eren; Saeid Karamzadeh; Mesut Kartal

doi:10.1016/j.dib.2023.109757

Radar human breathing dataset for applications of ambient assisted living and search and rescue operations

Cansu Eren^*
, Saeid Karamzadeh
, Mesut Kartal

^*Corresponding author for this work

Department of Electronics and Communication Engineering

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

This dataset consists of signatures of human vital signs that are recorded by ultrawideband radar and lidar sensors. The data acquisition scene considers the human posture models(supine/lateral/facedown), different radar antenna angles towards the human, various set of distances and operational radar characteristics (bandwidth selection/mean power). The raw data files of lidar&radar and processed data files are presented separately in the data repository. The lidar sensor is chosen as a reference sensor. There are 432 data records, and each data scene's trial number is eight. There is a homogeneous wooden table to mimic clutter while forming a dataset. Thus, this dataset covers applications of search and rescue operations, sleep monitoring, and ambient assisted living (AAL) applications.

Original language	English
Article number	109757
Journal	Data in Brief
Volume	51
DOIs	https://doi.org/10.1016/j.dib.2023.109757
Publication status	Published - Dec 2023

Bibliographical note

Publisher Copyright:
© 2023 The Author(s)

Funding

This study was supported by Istanbul Aydın University, Scientific Research Project (BAP) research fund in 2017.

Funders
Istanbul Aydın University

Keywords

Ambient assisted living, radar
Monitoring
Ultrawideband (UWB)
Vital signs

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10.1016/j.dib.2023.109757

Cite this

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abstract = "This dataset consists of signatures of human vital signs that are recorded by ultrawideband radar and lidar sensors. The data acquisition scene considers the human posture models(supine/lateral/facedown), different radar antenna angles towards the human, various set of distances and operational radar characteristics (bandwidth selection/mean power). The raw data files of lidar\&radar and processed data files are presented separately in the data repository. The lidar sensor is chosen as a reference sensor. There are 432 data records, and each data scene's trial number is eight. There is a homogeneous wooden table to mimic clutter while forming a dataset. Thus, this dataset covers applications of search and rescue operations, sleep monitoring, and ambient assisted living (AAL) applications.",

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AU - Eren, Cansu

AU - Karamzadeh, Saeid

AU - Kartal, Mesut

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Y1 - 2023/12

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AB - This dataset consists of signatures of human vital signs that are recorded by ultrawideband radar and lidar sensors. The data acquisition scene considers the human posture models(supine/lateral/facedown), different radar antenna angles towards the human, various set of distances and operational radar characteristics (bandwidth selection/mean power). The raw data files of lidar&radar and processed data files are presented separately in the data repository. The lidar sensor is chosen as a reference sensor. There are 432 data records, and each data scene's trial number is eight. There is a homogeneous wooden table to mimic clutter while forming a dataset. Thus, this dataset covers applications of search and rescue operations, sleep monitoring, and ambient assisted living (AAL) applications.

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KW - Vital signs

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ER -

Radar human breathing dataset for applications of ambient assisted living and search and rescue operations

Abstract

Bibliographical note

Funding

Keywords

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