Wearable Radar Sensor Measures Blood Pressure Continuously
|
By HospiMedica International staff writers Posted on 26 Feb 2020 |

Image: The CWR sensor that attaches to the sternum (Photo courtesy of Monash University)
A new study describes how two clip-on sensors attached to the sternum and earlobe can provide real-time blood pressure results.
Under development at Monash University (Melbourne, Australia), the novel measurement technique is based on radar sensor methodology. Instead of the traditional arm cuff, it uses a small continuous wave radar (CWR) sensor adhered to the sternum, and a photoplethysmogram sensor (PPG) clipped to the left earlobe. Using both sensors, the system measures pulse arrival time (PAT), pre-ejection period (PEP), and pulse transit time (PTT), and calculate continuous systolic blood pressure (SBP) from the data.
The researchers then collected experimental data from 43 subjects (40-65 years of age) in various static postures, as well as in 26 subjects doing six different exercise tasks, such as cycling on a stationary bike. Two mathematical models were then used to calculate SBP from the PTT/PAT data, and compare then to simultaneous sphygmomanometer readings. The results showed that for participants in the posture tasks, the best cumulative error percentage (CEP) was 92.28%, and for those in the exercises group, the best CEP was 82.61%. Additionally, removing PEP from PAT lead to a 9% improvement in results. The study was published on November 27, 2019, in Nature Scientific Reports.
“Clinicians still cannot continuously measure blood pressure during sleep, nor during times of activity such as walking or running. This means people with high, low, or irregular blood pressure can’t get the critical information they need about the state of their health around the clock,” said senior author Mehmet Yuce, PhD, of the department of electrical and computer systems engineering. “A wearable device that can provide comfort and portability while people are going about their daily lives will be a significant development for the health sector in Australia and internationally.”
CWR uses known radiofrequency (RF) energy that is transmitted and then received from any reflecting objects. Any movement of the transmitter, target, or both causes a change in the frequency of the electromagnetic wave, known as the Doppler shift. It is also possible to use CWR to measure range instead of range rate by frequency modulation. By measuring the frequency of the return signal, the time delay between transmission and reception can be measured.
Related Links:
Monash University
Under development at Monash University (Melbourne, Australia), the novel measurement technique is based on radar sensor methodology. Instead of the traditional arm cuff, it uses a small continuous wave radar (CWR) sensor adhered to the sternum, and a photoplethysmogram sensor (PPG) clipped to the left earlobe. Using both sensors, the system measures pulse arrival time (PAT), pre-ejection period (PEP), and pulse transit time (PTT), and calculate continuous systolic blood pressure (SBP) from the data.
The researchers then collected experimental data from 43 subjects (40-65 years of age) in various static postures, as well as in 26 subjects doing six different exercise tasks, such as cycling on a stationary bike. Two mathematical models were then used to calculate SBP from the PTT/PAT data, and compare then to simultaneous sphygmomanometer readings. The results showed that for participants in the posture tasks, the best cumulative error percentage (CEP) was 92.28%, and for those in the exercises group, the best CEP was 82.61%. Additionally, removing PEP from PAT lead to a 9% improvement in results. The study was published on November 27, 2019, in Nature Scientific Reports.
“Clinicians still cannot continuously measure blood pressure during sleep, nor during times of activity such as walking or running. This means people with high, low, or irregular blood pressure can’t get the critical information they need about the state of their health around the clock,” said senior author Mehmet Yuce, PhD, of the department of electrical and computer systems engineering. “A wearable device that can provide comfort and portability while people are going about their daily lives will be a significant development for the health sector in Australia and internationally.”
CWR uses known radiofrequency (RF) energy that is transmitted and then received from any reflecting objects. Any movement of the transmitter, target, or both causes a change in the frequency of the electromagnetic wave, known as the Doppler shift. It is also possible to use CWR to measure range instead of range rate by frequency modulation. By measuring the frequency of the return signal, the time delay between transmission and reception can be measured.
Related Links:
Monash University
Latest Critical Care News
- Inhaled Analgesic Matches Morphine for Prehospital Trauma Pain
- FDA Clears Tongue-Applied Neuromodulation System for Stroke Gait Rehabilitation
- Eye Test May Predict Return of Consciousness After Severe Brain Injury
- Medical Drone Program Improves Blood Access and Patient Survival
- AI System Enables Real-Time Sepsis Quality Assessment and Improves Adherence
- AI Detects Hidden ECG Marker of Sudden Cardiac Death
- FDA-Cleared AI Wearable Monitor Detects Opioid-Related Respiratory Risk in Hospitals
- Mitral Valve Repair Device Receives EU Approval for Functional Regurgitation
- AI Risk Score Reveals Hidden Hypertension-Related Organ Damage
- AI Tool Predicts Bronchopulmonary Dysplasia Risk in Preterm Infants
- Optical Brain Monitoring Predicts Neurodevelopmental Outcomes in Preterm Infants
- AI Tool Identifies Children With Pneumonia Requiring Hospital Care
- AI Ultrasound System Improves Safety of Blood–Brain Barrier Opening
- CE-Marked Smartphone AI Enables Autonomous Skin Cancer Assessment at Point of Care
- Handheld Optical Device Screens for Early Necrotizing Enterocolitis in Preterm Infants
- Home Blood Pressure Telemonitoring Linked to Fewer Cardiovascular Events
Channels
Artificial Intelligence
view channel
AI Trends Report Guides Responsible, Effective Healthcare Deployment
Hospitals are under growing pressure to adopt artificial intelligence tools that improve safety, efficiency, and continuity of care without compromising quality. At the same time, clinicians need clearer... Read more
Privacy-Preserving AI Protects Sensitive Information in ECG Data
Artificial intelligence applied to electrocardiography can extract more than cardiac rhythm. Algorithms can infer age, sex, race, and even identity from electrocardiogram (ECG) signals, creating privacy... Read moreSurgical Techniques
view channel
Aortic Arch Remodeling Device Improves Type I Dissection Repair
Acute DeBakey Type I aortic dissection is an emergent tear of the ascending aorta that can extend into the arch and descending thoracic aorta. Rapid ischemic complications and high early mortality make... Read more
Intravesical CAR T Therapy Shows Promise for Bladder Cancer Treatment
Bladder cancer is common and frequently recurs after initial therapy, exposing patients to repeated procedures and cumulative toxicity. High‑risk disease often progresses despite intravesical drugs or... Read morePatient Care
view channel
AI Avatar Doctor Improves Patient Understanding Before Radiotherapy
Radiation oncology consultations require patients to grasp complex concepts quickly, yet anxiety and information overload often undermine understanding and informed consent. Poor comprehension can also... Read more
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read moreHealth IT
view channel
Digital Heart Model Supports Targeted Ablation in Atrial Fibrillation
Atrial fibrillation is an erratic, quivering heartbeat and a leading cause of stroke. Catheter ablation is widely used to interrupt arrhythmogenic tissue, yet many patients—especially with persistent ... Read moreAI Framework Helps Clinicians Create Trustworthy Risk Prediction Tools
Artificial intelligence (AI) is increasingly used to estimate risks for conditions such as sepsis, heart disease, and cancer, yet many models remain difficult for clinicians to interpret or trust.... Read morePoint of Care
view channel
AI Dermatology Platform Targets Early Detection of Non-Melanoma Skin Cancer
Keratinocyte skin cancers, including basal cell and squamous cell carcinoma, account for a substantial share of dermatology workload in the United States and require accurate triage to guide biopsy decisions.... Read more







