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BACKGROUND: Vision-based pulmonary diagnostics present a unique approach for tracking and measuring natural breathing behaviors through remote imaging. While many existing methods correlate chest and diaphragm movements to respiratory behavior, we look at how the direct visualization of thermal CO2 exhale flow patterns can be tracked to directly measure expiratory flow. METHODS: In this work, we present a novel method for isolating and extracting turbulent exhale flow signals from thermal image sequences through flow-field prediction and optical flow measurement. The objective of this work is to introduce a respiratory diagnostic tool that can be used to capture and quantify natural breathing, to identify and measure respiratory metrics such as breathing rate, flow, and volume. One of the primary contributions of this work is a method for capturing and measuring natural exhale behaviors that describe individualized pulmonary traits. By monitoring subtle individualized respiratory traits, we can perform secondary analysis to identify unique personalized signatures and abnormalities to gain insight into pulmonary function. In our study, we perform data acquisition within a clinical setting to train an inference model (FieldNet) that predicts flow-fields to quantify observed exhale behaviors over time. RESULTS: Expiratory flow measurements capturing individualized flow signatures from our initial cohort demonstrate how the proposed flow field model can be used to isolate and analyze turbulent exhale behaviors and measure anomalous behavior. CONCLUSIONS: Our results illustrate that detailed spatial flow analysis can contribute to unique signatures for identifying patient specific natural breathing behaviors and abnormality detection. This provides the first-step towards a non-contact respiratory technology that directly captures effort-independent behaviors based on the direct measurement of imaged CO2 exhaled airflow patterns.

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OBJECTIVE: In this work, we introduce a quantitative non-contact respiratory evaluation method for fine-grain exhale flow and volume estimation through Thermal- CO2 imaging. This provides a form of respiratory analysis that is driven by visual analytics of exhale behaviors, creating quantitative metrics for exhale flow and volume modeled as open-air turbulent flows. This approach introduces a novel form of effort-independent pulmonary evaluation enabling behavioral analysis of natural exhale behaviors. METHODS: CO2 filtered infrared visualizations of exhale behaviors are used to obtain breathing rate, volumetric flow estimations (L/s) and per-exhale volume (L) estimations. We conduct experiments validating visual flow analysis to formulate two behavioral Long-Short-Term-Memory (LSTM) estimation models generated from visualized exhale flows targeting per-subject and cross-subject training datasets. RESULTS: Experimental model data generated for training on our per-individual recurrent estimation model provide an overall flow correlation estimate correlation of R2=0.912 and volume in-the-wild accuracy of 75.65-94.44%. Our cross-patient model extends generality to unseen exhale behaviors, obtaining an overall correlation of R2=0.804 and in-the-wild volume accuracy of 62.32-94.22%. CONCLUSION: This method provides non-contact flow and volume estimation through filtered CO2 imaging, enabling effort-independent analysis of natural breathing behaviors. SIGNIFICANCE: Effort-independent evaluation of exhale flow and volume broadens capabilities in pulmonological assessment and long-term non-contact respiratory analysis.

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BACKGROUND: The skin surface becomes wrinkled and rough due to various internal and external factors. A three-dimensional (3D) analysis of the skin is required to improve skin conditions. Stereophotogrammetry, a noninvasive 3D analysis method, is easy to install and use, but most stereo systems have a fixed baseline and scale. Previous stereo systems are not suitable for observing micro-range skin features. Therefore, we suggest the optimal conditions and methods for the 3D analysis of skin microrelief using a multi-conditioned stereo system. METHODS: We constructed a nonconvergence model using a mobile device and acquired stereo images under multiscale and multi-baseline conditions. We extracted 3D information of the skin through our process: preprocessing, skin feature extraction, feature matching, and actual depth mapping. We improved the accuracy of the 3D analysis of the skin by using disparity values instead of disparity maps. We compared and analyzed the performances of six local feature detector and descriptor algorithms. In addition, we suggested depth-mapping formulas to estimate the actual depth of the skin microrelief. RESULTS: We confirmed that stereo images with a working distance of 70-75 mm and a baseline of 4-8 mm are effective for the 3D analysis of skin microrelief. In addition, accelerated KAZE exhibited the best performance for features extraction and stereo matching. Finally, the extracted 3D information was converted to the actual depth, and the performance of the 3D analysis was verified. CONCLUSION: The proposed system and method that provide texture information are effective for 3D skin disease analysis and evaluation.

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Sports professionals have been increasingly using Virtual Reality (VR) for training and assessment of skill-based sports. Yet fundamental questions about the virtue of VR training for skill-based sports remain unanswered: Can the complex motor skills in these sports be learned in VR? If so, do these skills transfer to the real world? We have developed a VR table tennis system that incorporates customized physics with realistic audio-visual stimuli, haptics, and motion capture to enhance VR immersion and collect information about the player's posture and technique. We have assessed skill acquisition and training transfer by comparing real table tennis performance between a control group (n=7) that received no training and an experimental group (n=8) trained for five sessions in VR. Results show a significant improvement in technique but no significant changes in the number of the returned balls in the experimental group in the real-life retention session. However, no significant differences are found in the control group. Our findings support the notion that complex skills can be learned in VR and that obtained skills can transfer to the real world. This work offers an inexpensive VR table tennis training platform, enabling effective training via real-time motor and ball returning technique feedback.

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BACKGROUND: Studies that examine the growth effects of massage at ages beyond infancy are rare. A recently developed massage chair (BEG-100) targets teenagers who want to increase their growth. The chair can stretch areas around the knee after fixating the knee and ankle areas. METHODS: This is a clinical study that included 38 children aged 11 years whose heights ranged from 145.0 to 155.0 cm. We aim to observe the potential of a 24-week massage for growth promotion. We will also evaluate the changes in height percentile, height, height standard deviation score, bone age, height standard deviation score for bone age, growth rate, predicted height estimated from bone age, seated height-to-standing height ratio, weight, and body mass index. To confirm safety, the associated adverse events will be investigated. OBJECTIVE: The aim of this study was to investigate the growth-promoting effect of BEG-100 in children with average height. TRIAL REGISTRATION: KCT0004673 (Clinical Research Information Service).

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The ability to detect and diagnose neurocognitive disorders at the earliest possible moment is key to a better prognosis for the patient. Two of the earliest indicators of potential neurocognitive problems are motor and visual dysfunction. Motor disorders and problems in visual cognition can be seen in many neurocognitive disorders, resulting in abnormal physical reactions to visual stimuli. Analyzing physical behaviors when presented with such stimuli can provide insights into the visual perception and motor abilities of an individual, yet there is currently no unbiased, objective, general-purpose tool that analyzes attention and motor behavior to assess neurocognitive function. We propose a novel method of neurocognitive function assessment that tests the patient's cognition using virtual reality with eye tracking and motion analysis. By placing the patient in a controlled virtual environment and analyzing their movements, we can evoke certain physical responses from subjects for neurocognitive assessment. We have developed a prototype system that places the subject in a virtual baseball field and captures their full body motion as they try to catch baseballs. This scenario tests the subject's ability to determine the landing time and position of the ball, as well as the test subject's balance, motor skills, attention, and memory. Preliminary tests with 20 healthy normal individuals demonstrate the ability of this tool to assess the test subject's balance, memory, attention, and reaction to visual stimuli. This platform has a twofold contribution: it is used to assess several neurocognitive constructs that affect visual and motor capability neutrally and objectively based on controlled stimuli, and it enables objective comparison between different neurocognitive disorders research in this field.

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Expressions are a basic necessity for daily living, as they are required for managing relationships with other people. Conventional expression training has difficulty achieving an objective measurement, because their assessment depends on the therapist's ability to assess a patient's state or training effectiveness. In addition, it is difficult to provide emotional and social situations in the same manner for each training or assessment session. Virtual reality techniques can overcome shortcomings occurring in conventional studies by providing exact and objective measurements and emotional and social situations. In this study, we developed a virtual reality prototype that could present emotional situation and measure expression characteristics. Although this is a preliminary study, it could be considered that this study shows the potential of virtual reality as an assessment tool.

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