User's Breathing Research Articles

Virtual reality experiences for breathing and relaxation training: The effects of real vs. placebo biofeedback

Virtual reality biofeedback systems for relaxation training can be an effective tool for reducing stress and anxiety levels, but most of them offer a limited user experience associated to the execution of a single task and a biofeedback mechanism that reflects a single physiological measurement. Furthermore, user evaluations of such systems do not typically include a placebo condition, making it difficult to determine the actual contribution of biofeedback. This paper proposes a VR system for breathing and relaxation training that: (i) uses biofeedback mechanisms based on multiple physiological measurements, (ii) provides a richer user experience through a narrative that unfolds in phases where the user is the main character and controls different elements of the virtual environment through biofeedback. To evaluate the system and to assess the actual contribution of biofeedback, we compared two conditions involving 35 participants: a biofeedback condition that exploited real-time measurements of user's breathing, skin conductance, and heart rate; and a placebo control condition, in which changes in the virtual environment followed physiological values recorded from a session with another user. The results showed that the proposed virtual experience helped users relax in both conditions, but real biofeedback produced results that were superior to placebo biofeedback, in terms of both relaxation and sense of presence. These outcomes highlight the important role that biofeedback can play in virtual reality systems for relaxation training, as well as the need for researchers to consider placebo conditions in evaluating this kind of systems.

Mycelium as a self-growing biobased material for the fabrication of single-layer masks

Disposable face masks are an essential piece of personal protective equipment for workers in medical facilities, laboratories, and the general public to prevent the spread of illnesses and/or contamination. Covid-19 resulted in an uptick in the usage and production of face masks, exacerbating issues related to the waste and recycling of these materials. Traditionally, face masks are derived from petrochemicals, such as melt-blown or spunbound polypropylene. As such, there is a need to find sustainable mask materials that can maintain or improve the performance of petrochemical masks. This paper explores an alternative mask material that utilizes fungal mycelium as self-growing filaments to enhance the efficiency of individual polypropylene mask layers. By engineering the growth pattern and time, breathability and filtration efficiency was optimized such that one layer of the mycelium-modified mask could replace all three layers of the traditional three-layer mask. Additionally, it was found that the mycelium-modified mask exhibits asymmetric hydrophobicity, with super-hydrophobicity at the composite-air interface and lower hydrophobicity at the composite-medium interface. This property can improve the performance of the modified mask by protecting the mask from external liquids without trapping water vapor from the user's breath. The findings from this study can provide a basis for further development of mycelium to create sustainable filtration materials with enhanced functionality.

Rope Jumping Strength Monitoring on Smart Devices via Passive Acoustic Sensing.

Rope jumping, as a fitness exercise recommended by many sports medicine practitioners, can improve cardiorespiratory capacity and physical coordination. Existing rope jump monitoring systems have limitations in terms of convenience, comfort, and exercise intensity evaluation. This paper presents a rope jump monitoring system using passive acoustic sensing. Our system exploits the off-the-shelf smartphone and headphones to capture the user's rope-jumping sound and breathing sound after exercise. Given the captured acoustic data, the system uses a short-time energy-based approach and the high correlation between rope jumping cycles to detect the rope-jumping sound frames, then applies a dual-threshold endpoint detection algorithm to calculate the number of rope jumps. Finally, our system performs regression predictions of exercise intensity based on features extracted from the jumping speed and the mel spectrograms of the user's breathing sound. The significant advantage of the system lies in the solution of the problem of poorly characterized mel spectrograms. We employ an attentive mechanism-based GAN to generate optimized breathing sound mel spectrograms and apply domain adversarial adaptive in the network to improve the migration capability of the system. Through extensive experiments, our system achieves (on average) 0.32 and 2.3% error rates for the rope jumping count and exercise intensity evaluation, respectively.

Multi-sensory display of self-avatar's physiological state: virtual breathing and heart beating can increase sensation of effort in VR.

In this paper we explore the multi-sensory display of self-avatars' physiological state in Virtual Reality (VR), as a means to enhance the connection between the users and their avatar. Our approach consists in designing and combining a coherent set of visual, auditory and haptic cues to represent the avatar's cardiac and respiratory activity. These sensory cues are modulated depending on the avatar's simulated physical exertion. We notably introduce a novel haptic technique to represent respiratory activity using a compression belt simulating abdominal movements that occur during a breathing cycle. A series of experiments was conducted to evaluate the influence of our multi-sensory rendering techniques on various aspects of the VR user experience, including the sense of virtual embodiment and the sensation of effort during a walking simulation. A first study ($\mathrm{N}=30$) that focused on displaying cardiac activity showed that combining sensory modalities significantly enhances the sensation of effort. A second study ($\mathrm{N}=20$) that focused on respiratory activity showed that combining sensory modalities significantly enhances the sensation of effort as well as two sub-components of the sense of embodiment. Interestingly, the user's actual breathing tended to synchronize with the simulated breathing, especially with the multi-sensory and haptic displays. A third study ($\mathrm{N}=18$) that focused on the combination of cardiac and respiratory activity showed that combining both rendering techniques significantly enhances the sensation of effort. Taken together, our results promote the use of our novel breathing display technique and multi-sensory rendering of physiological parameters in VR applications where effort sensations are prominent, such as for rehabilitation, sport training, or exergames.

Humidity Sensing of Stretchable and Transparent Hydrogel Films for Wireless Respiration Monitoring

HighlightsA general strategy of fabricating thickness-controllable hydrogel films with diverse polymer networks for humidity sensing is proposed. The hydrogel film humidity sensor displays an unprecedented sensitivity up to 13,462.1%/%RH.The stretchable humidity sensor can work normally under large tensile strains with even enhanced sensitivity, which makes the humidity responding property of hydrogel mechanically programmable.A wireless respiratory interruption detection mask with Bluetooth transmission function is developed based on the sensor, enabling the real-time, wireless and accurate acquisition of user's breathing state, such as the interval and breathing frequency and apnea.

Non-contact breath cycle analysis for different breathing patterns using RGB-D videos

Traditionally, yogic breathing exercises have been considered an effective adjunct in managing stress, chronic pain and depression. Real-time bio-feedback based gaming applications can provide an opportunity to broaden the reach of yogic breathing exercises. To extract the bio-feedback parameters on human breathing behavior, robust real-time quantification of inhalation, exhalation, and retention durations for each breath cycle is very crucial. This paper implements the extraction of every respiration cycle of a person along with the duration of inhalation and exhalation using RGB-D videos under minimal movement. The proposed method uses the abdominal-thoracic region as the region of interest (ROI) and relates the small displacement of the chest region with breath and obtains a time-series signal that represents the user's breathing pattern. Appropriate digital filtering techniques are employed in eliminating the noise components and a novel algorithm is proposed to extract individual breath cycle parameters. From the extracted parameters, a gamified bio-feedback application to regulate respiration in real-time is demonstrated. The proposed methodology is evaluated for different breathing patterns against a collected representative dataset, which includes ten participants of different age groups and gender. Results indicate that the breathing rate can be detected with a mean RMSE error of 0.435 s and 0.467 s for the inhalation and exhalation times between the proposed method and the ground truth measurement.

Surface modified highly porous egg-shell membrane derived granular activated carbon coated on paper substrate and its humidity sensing properties

Herein, we report a highly porous granular activated carbon (AC) from the biowaste of hen egg-shell membrane (HEM) for the detection of relative humidity (RH) using cellulose paper as substrate. As a novel strategy, the present AC is prepared through solvent-free thermal activation at high temperature in N2 atmosphere. No other chemical or surfactants were used for activation. The present AC derived from HEM exhibits both microporous and mesoporous structure with good sorption properties as exposed by TEM and BET studies. Accordingly, the adsorptivity of present AC is envisioned to act as an effective humidity sensor. The sensor response to RH varied from 10 to 90% shows the rapid response and recovery times (4/14 s). The high water uptake of highly porous HEM derived AC with Nafion improves the ionic conductivity (through protonation) at low to high humid air. Furthermore, the present sensor enables to detect the modulation of moisture air from user's speech and breath from the perspective of real-time monitoring. The salient features of this eco-friendly sensor is its high sensitivity, reliability, and rapid response that makes it a promising candidate for flexible sensor devices.

Breath-Triggered Haptic and Acoustic Guides to Support Effortless Calm Breathing.

Stress is a common issue in today's society and can be caused by a variety of triggers in activities such as work or driving. Various negative consequences can arise of stress such as reduced job productivity, sleep disorders, or physiological diseases like depression or anxiety. A popular approach to manage stress is voluntary deep and slow breathing. However, deliberate deep breathing requires conscious attention and effort, and thus often interferes with daily activities such as working and driving. We present a system that monitors the user's breathing in real-time and provides rhythmical feedback to support effortless and unconscious slow breathing in everyday-life. Our system comprises three feedback modes: 1.) acoustic feedback, 2.) haptic feedback, and 3.) mixed feedback combining both modalities. We apply our system in a driver setting and conduct a user study with twelve participants to evaluate the effects of our intervention on users' physiology and perception. We find that acoustic and mixed guiding can reduce breathing pace without affecting focus, which suggests that subtle rhythmical feedback is a promising approach to reduce breathing pace and thus counteract stress.

Accurate Respiration Monitoring for Mobile Users With Commercial RFID Devices

Vital signs (e.g., respiration rate or heartbeat rate) sensing is of great importance to implement pervasive in-home healthcare. Traditional vital signs monitoring approaches usually require users to wear some dedicated sensors. These approaches are intrusive and inconvenient to use, especially for elderly people. Some non-intrusive vital signs monitoring approaches based on wireless sensing have been proposed in recent years. However, these approaches require the target user to be in situ during the monitoring process, which greatly limits their utilization in practical scenarios where the target users usually move around. In this paper, we propose RF-RMM, an RFID-based approach to accurate and continuous respiration monitoring for mobile users. The major challenge in respiration monitoring for moving people is that the tiny body displacement caused by the user's respiration is overwhelmed by the user's entire body movement. To address this issue, we propose a novel approach that uses a pair of tags to eliminate the effect of the user's body movement. We fuse the data from the paired tags to cancel the effect of the user's entire body movement and retain only the displacement caused by the user's respiration. Another challenging issue in implementing RF-RMM is how to resolve the phase ambiguity problem when the target user moves around, which becomes more serious than in the static case. We propose a distance tracking algorithm to track the phase transition during the user's movement, according to which the phase ambiguity problem can be well handled. We implement RF-RMM on commercial RFID devices and conduct extensive real-world experiments to evaluate its performance. The results show that RF-RMM achieves accurate respiration rate monitoring with an average error of 0.54 BPM in estimating different users' respiration rate and an average relative error of less than 13% in estimating the user's individual breath length.

Vital Signs Monitoring with RFID: Opportunities and Challenges

Vital signs monitoring plays an important role in health assessing, especially for elderly healthcare. Traditional vital signs monitoring systems are intrusive. They require the users to wear or attach dedicated sensors and thus are inconvenient to use. Although recently developed contactless vital signs monitoring approaches (e.g., those based on WiFi sensing) become friendly, they cannot differentiate multiple target users. This article envisions the opportunity of utilizing the radio frequency identification (RFID) technology to perform accurate vital signs monitoring, which can combine the merit of contactless convenience as well as the advantage in distinguishing different users. We introduce the basic ideas of using RFID to perform vital signs monitoring and discuss the challenges to be addressed before the ideas can be put into practice. With commodity RFID devices, we implement a breath monitoring prototype that can accurately monitor the user's breath even when the user is moving. The prototype achieves over 97 percent accuracy in estimating breath rate and below 8 percent error in estimating individual breath length.

Multimedia-Assisted Breathwalk-Aware System

Breathwalk is a science of combining specific patterns of footsteps synchronized with the breathing. In this study, we developed a multimedia-assisted Breathwalk-aware system which detects user's walking and breathing conditions and provides appropriate multimedia guidance on the smartphone. Through the mobile device, the system enhances user's awareness of walking and breathing behaviors. As an example application in slow technology, the system could help meditator beginners learn "walking meditation," a type of meditation which aims to be as slow as possible in taking pace, to synchronize footstep with breathing, and to land every footstep with toes first. In the pilot study, we developed a walking-aware system and evaluated whether multimedia-assisted mechanism is capable of enhancing beginner's walking awareness while walking meditation. Experimental results show that it could effectively assist beginners in slowing down the walking speed and decreasing incorrect footsteps. In the second experiment, we evaluated the Breathwalk-aware system to find a better feedback mechanism for learning the techniques of Breathwalk while walking meditation. The experimental results show that the visual-auditory mechanism is a better multimedia-assisted mechanism while walking meditation than visual mechanism and auditory mechanism.