Mobile Thermal Imaging Software Monitors Breathing
|
By MedImaging International staff writers Posted on 28 Sep 2017 |

Image: Research suggests low-cost thermal cameras attached to mobile phones can track breathing patterns (Photo courtesy of Youngjun Cho / UCL).
Novel algorithms could allow portable, low-cost thermal cameras connected to mobile devices to detect breathing problems and monitor stress.
Researchers at University College London (UCL; United Kingdom) have developed a novel approach for respiration tracking which observes the human nostril, using local temperature variations to infer inhalation and exhalation cycles. Three methods are involved; an adaptive technique that quantifies and constructs a color mapping of absolute temperature that improves segmentation, classification and tracking; a thermal gradient flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking; and a thermal voxel method that increases the reliability of the captured respiration signals, compared to the traditional averaging method.
The researchers demonstrated the robustness of the system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes, and also showed how the algorithm outperformed standard photoplethysmography (PPG) algorithms in settings with different amounts of environmental thermal changes and human motion. The new system also compensates for the negative effects of variations in the ambient temperature and motion artifacts. The study was published on September 13, 2017, In Biomedical Optics Express.
“As thermal cameras continue to get smaller and less expensive, we expect that phones, computers and augmented reality devices will one day incorporate thermal cameras that can be used for various applications,” said senior author Nadia Bianchi-Berthouze, PhD. “By using low-cost thermal cameras, our work is a first step toward bringing thermal imaging into people's everyday lives. This approach can be used in places other sensors might not work or would cause concern.”
“Thermal cameras can detect breathing at night and during the day without requiring the person to wear any type of sensor. Compared to a traditional video camera, a thermal camera is more private because it is more difficult to identify the person,” said lead author PhD candidate Youngjun Cho. “We wanted to use the new portable systems to do the same thing by creating a smartphone based respiratory tracking method that could be used in almost any environment or activity.”
Respiration rate is a critical vital sign that provides early identification of respiratory compromise and patient distress, and is especially important for post-surgical patients receiving patient-controlled analgesia (PCA) for pain management, as the sedation can induce respiratory depression and place patients at considerable risk of serious injury or even death.
Related Links:
University College London
Researchers at University College London (UCL; United Kingdom) have developed a novel approach for respiration tracking which observes the human nostril, using local temperature variations to infer inhalation and exhalation cycles. Three methods are involved; an adaptive technique that quantifies and constructs a color mapping of absolute temperature that improves segmentation, classification and tracking; a thermal gradient flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking; and a thermal voxel method that increases the reliability of the captured respiration signals, compared to the traditional averaging method.
The researchers demonstrated the robustness of the system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes, and also showed how the algorithm outperformed standard photoplethysmography (PPG) algorithms in settings with different amounts of environmental thermal changes and human motion. The new system also compensates for the negative effects of variations in the ambient temperature and motion artifacts. The study was published on September 13, 2017, In Biomedical Optics Express.
“As thermal cameras continue to get smaller and less expensive, we expect that phones, computers and augmented reality devices will one day incorporate thermal cameras that can be used for various applications,” said senior author Nadia Bianchi-Berthouze, PhD. “By using low-cost thermal cameras, our work is a first step toward bringing thermal imaging into people's everyday lives. This approach can be used in places other sensors might not work or would cause concern.”
“Thermal cameras can detect breathing at night and during the day without requiring the person to wear any type of sensor. Compared to a traditional video camera, a thermal camera is more private because it is more difficult to identify the person,” said lead author PhD candidate Youngjun Cho. “We wanted to use the new portable systems to do the same thing by creating a smartphone based respiratory tracking method that could be used in almost any environment or activity.”
Respiration rate is a critical vital sign that provides early identification of respiratory compromise and patient distress, and is especially important for post-surgical patients receiving patient-controlled analgesia (PCA) for pain management, as the sedation can induce respiratory depression and place patients at considerable risk of serious injury or even death.
Related Links:
University College London
Latest General/Advanced Imaging News
- New 3D Imaging System Addresses MRI, CT and Ultrasound Limitations
- AI-Based Tool Predicts Future Cardiovascular Events in Angina Patients
- AI-Based Tool Accelerates Detection of Kidney Cancer
- New Algorithm Dramatically Speeds Up Stroke Detection Scans
- 3D Scanning Approach Enables Ultra-Precise Brain Surgery
- AI Tool Improves Medical Imaging Process by 90%
- New Ultrasmall, Light-Sensitive Nanoparticles Could Serve as Contrast Agents
- AI Algorithm Accurately Predicts Pancreatic Cancer Metastasis Using Routine CT Images
- Cutting-Edge Angio-CT Solution Offers New Therapeutic Possibilities
- Extending CT Imaging Detects Hidden Blood Clots in Stroke Patients
- Groundbreaking AI Model Accurately Segments Liver Tumors from CT Scans
- New CT-Based Indicator Helps Predict Life-Threatening Postpartum Bleeding Cases
- CT Colonography Beats Stool DNA Testing for Colon Cancer Screening
- First-Of-Its-Kind Wearable Device Offers Revolutionary Alternative to CT Scans
- AI-Based CT Scan Analysis Predicts Early-Stage Kidney Damage Due to Cancer Treatments
- CT-Based Deep Learning-Driven Tool to Enhance Liver Cancer Diagnosis
Channels
Radiography
view channel
Routine Mammograms Could Predict Future Cardiovascular Disease in Women
Mammograms are widely used to screen for breast cancer, but they may also contain overlooked clues about cardiovascular health. Calcium deposits in the arteries of the breast signal stiffening blood vessels,... Read more
AI Detects Early Signs of Aging from Chest X-Rays
Chronological age does not always reflect how fast the body is truly aging, and current biological age tests often rely on DNA-based markers that may miss early organ-level decline. Detecting subtle, age-related... Read moreMRI
view channel
MRI Scans Reveal Signature Patterns of Brain Activity to Predict Recovery from TBI
Recovery after traumatic brain injury (TBI) varies widely, with some patients regaining full function while others are left with lasting disabilities. Prognosis is especially difficult to assess in patients... Read more
Novel Imaging Approach to Improve Treatment for Spinal Cord Injuries
Vascular dysfunction in the spinal cord contributes to multiple neurological conditions, including traumatic injuries and degenerative cervical myelopathy, where reduced blood flow can lead to progressive... Read more
AI-Assisted Model Enhances MRI Heart Scans
A cardiac MRI can reveal critical information about the heart’s function and any abnormalities, but traditional scans take 30 to 90 minutes and often suffer from poor image quality due to patient movement.... Read more
AI Model Outperforms Doctors at Identifying Patients Most At-Risk of Cardiac Arrest
Hypertrophic cardiomyopathy is one of the most common inherited heart conditions and a leading cause of sudden cardiac death in young individuals and athletes. While many patients live normal lives, some... Read moreUltrasound
view channel
Wearable Ultrasound Imaging System to Enable Real-Time Disease Monitoring
Chronic conditions such as hypertension and heart failure require close monitoring, yet today’s ultrasound imaging is largely confined to hospitals and short, episodic scans. This reactive model limits... Read more
Ultrasound Technique Visualizes Deep Blood Vessels in 3D Without Contrast Agents
Producing clear 3D images of deep blood vessels has long been difficult without relying on contrast agents, CT scans, or MRI. Standard ultrasound typically provides only 2D cross-sections, limiting clinicians’... Read moreNuclear Medicine
view channel
Radiopharmaceutical Molecule Marker to Improve Choice of Bladder Cancer Therapies
Targeted cancer therapies only work when tumor cells express the specific molecular structures they are designed to attack. In urothelial carcinoma, a common form of bladder cancer, the cell surface protein... Read more
Cancer “Flashlight” Shows Who Can Benefit from Targeted Treatments
Targeted cancer therapies can be highly effective, but only when a patient’s tumor expresses the specific protein the treatment is designed to attack. Determining this usually requires biopsies or advanced... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read morePatient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more







