Abstract

A wide range of wearable sensors exist on the market for continuous physiological health monitoring. The type and scope of health data that can be gathered is a function of the sensor modality. Blumio presents a dataset of synchronized data from a reference blood pressure device along with several wearable sensor types: PPG, applanation tonometry, and the Blumio millimeter-wave radar. Data collection was conducted under set protocol with subjects seated at rest. 115 study subjects were included (age range 20-67 years), resulting in over 19 hours of data acquired.

Instructions:

Participant Recruitment

Potential participants were informed of the study protocol prior to being enrolled. To be included in the study, subjects had to be over the age of 18 and under the age of 90. Informed consent was obtained from all participants. Personal data such as age, gender, height, and weight were collected prior to data collection and this information, along with collected sensor readings, was deidentified and stored in conformation with HIPAA.

Data Collection System

Blumio has conducted previous studies measuring arterial pulsations at the radial artery with millimeter-wave FMCW radar [1]. For this study, the developmental stage BGT60TR24B FMCW system (Infineon Technologies AG, Munich, Germany) was worn over the left wrist.

The data collection system also included the CNAP Monitor 500 (CNSystems Medizintechnik GmbH, Graz, Austria) worn on the left arm, a SPT-301 applanation tonometer (Millar Inc, Houston, USA) worn on the right wrist, and a SS4LA PPG transducer (BIOPAC Systems Inc, Goleta, USA) worn on the right hand’s middle digit.

Data Collection Procedures

Study protocol was approved by Western IRB prior to participant recruitment (Western IRB #20193057). All measurements were collected at the Blumio Office in San Mateo, CA. Measurements were performed according to a fixed protocol. Participants were seated at an appropriate height with both arms resting comfortably on a table in front of them. They were asked to rest quietly for 5 minutes in that position. Then, signals from the sensors were recorded simultaneously for a period of 10 minutes. During the signal acquisition period, the participant was asked to maintain a normal breathing frequency and to not speak or move.

Signal Processing

Following collection, the signals were first time-synchronized and then processed according to the steps described below.

The raw IF radar data output was processed utilizing two approaches. First, a standard phase transformation was used. This consisted of performing a Fast Fourier Transform (FFT) on the IF signal and extracting the phase from the appropriate range bin as described in our previous work. Secondly, a proprietary transformation created by Blumio was utilized. The algorithms employ a set of pre-processing and noise-reduction procedures, during which the radar signal is transformed into a univariate pulse waveform.

The auxiliary signals and the reference blood pressure data was extracted from the MP36R unit using the companion AcqKnowledge software (BIOPAC Systems Inc, Goleta, USA).

Dataset Description and Usage Notes

The entire dataset and associated participant health information are freely available for download as a ZIP file. All the sensor data is stored in CSV format. Each CSV file is named after the participant’s assigned identifier. The first column of the CSV contains the timestamp in seconds. For the sake of data analysis, all sensor channels have been time aligned in the included files. The second column includes the reference blood pressure in mmHg from the CNIBP monitor. The third column is data from the PPG sensor in mV. The fourth column includes the is the data from the applanation tonometer also in mV. The fifth column is the output from Blumio’s proprietary radar transform algorithm in arbitrary units. The sixth column is the output from the phase radar transformation algorithm in radians. Note that each file varies in length of time. Certain files have a truncated start due to the CNAP Monitor 500’s initialization period.

The included participant health information is available in a XSLX summary sheet. The information in the XSLX sheet is tabulated by participant study identifier.

Acknowledgment

The authors would like to thank the Silicon Valley Innovation Center (SVIC) and the Power & Sensor Systems (PSS) teams at Infineon Technologies AG for providing engineering support during our R&D process.

Funding

This work was supported by the Center for Disease Control under grant number 9679554 and Infineon Technologies AG.

References

[1] J. Johnson, C. Kim, and O. Shay, "Arterial Pulse Measurement with Wearable Millimeter Wave Device," in IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN), 2019, pp. 1-4.