Journal: Sensors (Basel, Switzerland)

Article Title: Driver Head–Hand Cooperative Action Recognition Based on FMCW Millimeter-Wave Radar and Deep Learning

doi: 10.3390/s25082399

Figure Lengend Snippet: Experimental setup: connection between the AWR1843BOOST radar sensor and the DCA1000EVM data acquisition board.

Article Snippet: The main equipment for this experiment consisted of the AWR1843BOOST millimeter-wave radar sensor [ ] and the DCA1000EVM [ ] data acquisition board from Texas Instruments.

Techniques:

Journal: Data in Brief

Article Title: Millimeter-wave radar based sleep posture transition dataset: SPT

doi: 10.1016/j.dib.2025.111471

Figure Lengend Snippet:

Article Snippet: Data collection , Data were collected using a millimeter-wave radar system (Texas Instruments IWR6843ISK-ODS) with a data acquisition board (DCA1000 EVM FPGA), a sensor carrier card (MMWAVEICBOOST), and control software (mmWave Studio). The radar was placed 1.5 m above the ground, aligned with the bed. Twenty volunteers (19–25 years, 45–90 kg) performed seven predefined posture transitions in a fixed order, each repeated 10 times, totaling 1,400 samples. A 10–15 s rest period was given between transitions. Volunteers started in a supine position at the bed center to ensure full radar coverage..

Techniques: Transformation Assay, Control, Software

Journal: Data in Brief

Article Title: Millimeter-wave radar based sleep posture transition dataset: SPT

doi: 10.1016/j.dib.2025.111471

Figure Lengend Snippet:

Article Snippet: As shown in , the millimeter-wave radar data acquisition system consists of three core modules: the millimeter-wave radar evaluation board (Texas Instruments IWR6843ISK-ODS), the millimeter-wave sensor bearer card platform (MMWAVEICBOOST), and the real-time high-speed data Acquisition Adapter (DCA1000).

Techniques: Transformation Assay, Control, Software