Impact of Biological Sex on Radar-Measured Heart Sound Quality.

Radar based contact-free technology has number of potential applications for monitoring the cardiopulmonary functions of patients. However, no study has evaluated the effect of gender on the quality of the recordings. This study makes an attempt to distinguish radar based recording of male and female subjects. The study analysed a publicly available dataset of radar-recorded heart sound signals from both male and female subjects. Here, we exploit the reference signal-to-noise ratio (RSNR) to quantify the signal's quality. The results indicate that there is a significant difference in the signal quality between males and females, with males having a higher RSNR value compared to females. This could be a limitation in the widespread use of the current radar based cardiopulmonary recording techniques and overcoming this should be considered for future research.Clinical relevance- This work has highlighted the gender based difference. By considering this, the radar based cardiopulmonary device has the potential for being used for patients requiring long-term monitoring.

Region-wise severity analysis of diabetic plantar foot thermograms.

OBJECTIVES: Diabetic foot ulcers (DFU) can be avoided if symptoms of diabetic foot complications are detected early and treated promptly. Early detection requires regular examination, which might be limited for many reasons. To identify affected or potentially affected regions in the diabetic plantar foot, the region-wise severity of the plantar foot must be known. METHODS: A novel thermal diabetic foot dataset of 104 subjects was developed that is suitable for Indian healthcare conditions. The entire plantar foot thermogram is divided into three parts, i.e., forefoot, midfoot, and hindfoot. The division of plantar foot is based on the prevalence of foot ulcers and the load on the foot. To classify the severity levels, conventional machine learning (CML) techniques like logistic regression, decision tree, KNN, SVM, random forest, etc., and convolutional neural networks (CNN), such as EfficientNetB1, VGG-16, VGG-19, AlexNet, InceptionV3, etc., were applied and compared for robust outcomes. RESULTS: The study successfully developed a thermal diabetic foot dataset, allowing for effective classification of diabetic foot ulcer severity using the CML and CNN techniques. The comparison of different methods revealed variations in performance, with certain approaches outperforming others. CONCLUSIONS: The region-based severity analysis offers valuable insights for targeted interventions and preventive measures, contributing to a comprehensive assessment of diabetic foot ulcer severity. Further research and development in these techniques can enhance the detection and management of diabetic foot complications, ultimately improving patient outcomes.

Non-contact respiratory rate monitoring using thermal and visible imaging: a pilot study on neonates.

Respiratory rate (RR) monitoring is essential in neonatal intensive care units. Despite its importance, RR is still monitored intermittently by manual counting instead of continuous monitoring due to the risk of skin damage with prolonged use of contact electrodes in preterm neonates and false signals due to displacement of electrodes. Thermal imaging has recently gained significance as a non-contact method for RR detection because of its many advantages. However, due to the lack of information in thermal images, the selection and tracking of the region of interest (ROI) in thermal images for neonates are challenging. This paper presents the integration of visible (RGB) and thermal (T) image sequences for the selection and tracking of ROI for breathing rate extraction. The deep-learning based tracking-by-detection approach is employed to detect the ROI in the RGB images, and it is mapped to the thermal images using the RGB-T image registration. The mapped ROI in thermal spectrum sequences gives the respiratory rate. The study was conducted first on healthy adults in different modes, including steady, motion, talking, and variable respiratory order. Subsequently, the method is tested on neonates in a clinical settings. The findings have been validated with a contact-based reference method.The average absolute error between the proposed and belt-based contact method in healthy adults reached 0.1 bpm and for more challenging conditions was approximately 1.5 bpm and 1.8 bpm, respectively. In the case of neonates, the average error is 1.5 bpm, which are promising results. The Bland-Altman analysis showed a good agreement of estimated RR with the reference method RR and this pilot study provided the evidence of using the proposed approach as a contactless method for the respiratory rate detection of neonates in clinical settings.

Thermal imaging in total knee replacement and its relation with inflammation markers.

Total knee replacement is an end-stage surgical treatment of osteoarthritis patients to improve their quality of life. The study presents a thermal imaging-based approach to assess the recovery of operated-knees. The study focuses on the potential of thermal imaging for total knee replacement and its relation with clinical inflammatory markers. A total of 20 patients with bilateral knee replacement were included for thermal imaging and serology, where data was acquired on pre-operative day and five post-operative days. To quantify the inflammation, the temperature-based parameters (like mean differential temperature, relative percentage of raised temperature) were evaluated from thermal images, while the clinically proven inflammation markers were obtained from blood samples for clinical validation. Initially, the knee region was segmented by applying the automatic method, subsequently, the mean skin temperature was calculated and investigated for a statistical relevant relationship with inflammatory markers. After surgery, the mean skin temperature was first increased (>2.15 ℃ for different views) then settled to pre-operative level by 90th day. Consequently, the mean differential temperature showed a strong correlation with erythrocyte sedimentation rate (r > 0.893) and C-reactive protein (r > 0.955). Also, the visual profile and relative percentage of raised temperature showed promising results in quantifying the temperature changes both qualitatively and quantitatively. This study provides an automatic and non-invasive way of screening the patients for raised levels of skin temperature, which can be a sign of inflammation. Hence, the proposed temperature-based technique can help the clinicians for visual assessment of post-operative recovery of patients.

Non-contact breathing rate monitoring in newborns: A review.

The neonatal period - the first 4 weeks of life - is the most critical time for a child's survival. Breathing rate is a vital indicator of the health condition and requires continuous monitoring in case of sickness or preterm birth. Breathing movements can be counted by contact and non-contact methods. In the case of newborn infants, the non-contact breathing rate monitoring need is high, as a contact-based approach may interfere while providing care and is subject to interference by non-breathing movements. This review article delivers a factual summary, and describes the methods and processing involved in non-contact based breathing rate monitoring. The article also provides the advantages, limitations, and clinical applications of these methods. Additionally, signal processing, feasibility, and future direction of different non-contact neonatal breathing rate monitoring are discussed.