In-Home Smartphone-Based Prediction of Obstructive Sleep Apnea in Conjunction With Level 2 Home Polysomnography.

Importance: Consumer-level sleep analysis technologies have the potential to revolutionize the screening for obstructive sleep apnea (OSA). However, assessment of OSA prediction models based on in-home recording data is usually performed concurrently with level 1 in-laboratory polysomnography (PSG). Establishing the predictability of OSA using sound data recorded from smartphones based on level 2 PSG at home is important. Objective: To validate the performance of a prediction model for OSA using breathing sound recorded from smartphones in conjunction with level 2 PSG at home. Design, Setting, and Participants: This diagnostic study followed a prospective design, involving participants who underwent unattended level 2 home PSG. Breathing sounds were recorded during sleep using 2 smartphones, one with an iOS operating system and the other with an Android operating system, simultaneously with home PSG in participants' own home environment. Participants were 19 years and older, slept alone, and had either been diagnosed with OSA or had no previous diagnosis. The study was performed between February 2022 and February 2023. Main Outcomes and Measures: Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the predictive model based on the recorded breathing sounds. Results: Of the 101 participants included during the study duration, the mean (SD) age was 48.3 (14.9) years, and 51 (50.5%) were female. For the iOS smartphone, the sensitivity values at apnea-hypopnea index (AHI) levels of 5, 15, and 30 per hour were 92.6%, 90.9%, and 93.3%, respectively, with specificities of 84.3%, 94.4%, and 94.4%, respectively. Similarly, for the Android smartphone, the sensitivity values at AHI levels of 5, 15, and 30 per hour were 92.2%, 90.0%, and 92.9%, respectively, with specificities of 84.0%, 94.4%, and 94.3%, respectively. The accuracy for the iOS smartphone was 88.6%, 93.3%, and 94.3%, respectively, and for the Android smartphone was 88.1%, 93.1%, and 94.1% at AHI levels of 5, 15, and 30 per hour, respectively. Conclusions and Relevance: This diagnostic study demonstrated the feasibility of predicting OSA with a reasonable level of accuracy using breathing sounds obtained by smartphones during sleep at home.

Accuracy of 11 Wearable, Nearable, and Airable Consumer Sleep Trackers: Prospective Multicenter Validation Study.

BACKGROUND: Consumer sleep trackers (CSTs) have gained significant popularity because they enable individuals to conveniently monitor and analyze their sleep. However, limited studies have comprehensively validated the performance of widely used CSTs. Our study therefore investigated popular CSTs based on various biosignals and algorithms by assessing the agreement with polysomnography. OBJECTIVE: This study aimed to validate the accuracy of various types of CSTs through a comparison with in-lab polysomnography. Additionally, by including widely used CSTs and conducting a multicenter study with a large sample size, this study seeks to provide comprehensive insights into the performance and applicability of these CSTs for sleep monitoring in a hospital environment. METHODS: The study analyzed 11 commercially available CSTs, including 5 wearables (Google Pixel Watch, Galaxy Watch 5, Fitbit Sense 2, Apple Watch 8, and Oura Ring 3), 3 nearables (Withings Sleep Tracking Mat, Google Nest Hub 2, and Amazon Halo Rise), and 3 airables (SleepRoutine, SleepScore, and Pillow). The 11 CSTs were divided into 2 groups, ensuring maximum inclusion while avoiding interference between the CSTs within each group. Each group (comprising 8 CSTs) was also compared via polysomnography. RESULTS: The study enrolled 75 participants from a tertiary hospital and a primary sleep-specialized clinic in Korea. Across the 2 centers, we collected a total of 3890 hours of sleep sessions based on 11 CSTs, along with 543 hours of polysomnography recordings. Each CST sleep recording covered an average of 353 hours. We analyzed a total of 349,114 epochs from the 11 CSTs compared with polysomnography, where epoch-by-epoch agreement in sleep stage classification showed substantial performance variation. More specifically, the highest macro F1 score was 0.69, while the lowest macro F1 score was 0.26. Various sleep trackers exhibited diverse performances across sleep stages, with SleepRoutine excelling in the wake and rapid eye movement stages, and wearables like Google Pixel Watch and Fitbit Sense 2 showing superiority in the deep stage. There was a distinct trend in sleep measure estimation according to the type of device. Wearables showed high proportional bias in sleep efficiency, while nearables exhibited high proportional bias in sleep latency. Subgroup analyses of sleep trackers revealed variations in macro F1 scores based on factors, such as BMI, sleep efficiency, and apnea-hypopnea index, while the differences between male and female subgroups were minimal. CONCLUSIONS: Our study showed that among the 11 CSTs examined, specific CSTs showed substantial agreement with polysomnography, indicating their potential application in sleep monitoring, while other CSTs were partially consistent with polysomnography. This study offers insights into the strengths of CSTs within the 3 different classes for individuals interested in wellness who wish to understand and proactively manage their own sleep.

Real-Time Detection of Sleep Apnea Based on Breathing Sounds and Prediction Reinforcement Using Home Noises: Algorithm Development and Validation.

BACKGROUND: Multinight monitoring can be helpful for the diagnosis and management of obstructive sleep apnea (OSA). For this purpose, it is necessary to be able to detect OSA in real time in a noisy home environment. Sound-based OSA assessment holds great potential since it can be integrated with smartphones to provide full noncontact monitoring of OSA at home. OBJECTIVE: The purpose of this study is to develop a predictive model that can detect OSA in real time, even in a home environment where various noises exist. METHODS: This study included 1018 polysomnography (PSG) audio data sets, 297 smartphone audio data sets synced with PSG, and a home noise data set containing 22,500 noises to train the model to predict breathing events, such as apneas and hypopneas, based on breathing sounds that occur during sleep. The whole breathing sound of each night was divided into 30-second epochs and labeled as "apnea," "hypopnea," or "no-event," and the home noises were used to make the model robust to a noisy home environment. The performance of the prediction model was assessed using epoch-by-epoch prediction accuracy and OSA severity classification based on the apnea-hypopnea index (AHI). RESULTS: Epoch-by-epoch OSA event detection showed an accuracy of 86% and a macro F1-score of 0.75 for the 3-class OSA event detection task. The model had an accuracy of 92% for "no-event," 84% for "apnea," and 51% for "hypopnea." Most misclassifications were made for "hypopnea," with 15% and 34% of "hypopnea" being wrongly predicted as "apnea" and "no-event," respectively. The sensitivity and specificity of the OSA severity classification (AHI≥15) were 0.85 and 0.84, respectively. CONCLUSIONS: Our study presents a real-time epoch-by-epoch OSA detector that works in a variety of noisy home environments. Based on this, additional research is needed to verify the usefulness of various multinight monitoring and real-time diagnostic technologies in the home environment.

General-Purpose Ultrasound Neuromodulation System for Chronic, Closed-Loop Preclinical Studies in Freely Behaving Rodents.

Transcranial focused ultrasound stimulation (tFUS) is an effective noninvasive treatment modality for brain disorders with high clinical potential. However, the therapeutic effects of ultrasound neuromodulation are not widely explored due to limitations in preclinical systems. The current preclinical studies are head-fixed, anesthesia-dependent, and acute, limiting clinical translatability. Here, this work reports a general-purpose ultrasound neuromodulation system for chronic, closed-loop preclinical studies in freely behaving rodents. This work uses microelectromechanical systems (MEMS) technology to design and fabricate a small and lightweight transducer capable of artifact-free stimulation and simultaneous neural recording. Using the general-purpose system, it can be observed that state-dependent ultrasound neuromodulation of the prefrontal cortex increases rapid eye movement (REM) sleep and protects spatial working memory to REM sleep deprivation. The system will allow explorative studies in brain disease therapeutics and neuromodulation using ultrasound stimulation for widespread clinical adoption.

The impact of CT image parameters and skull heterogeneity modeling on the accuracy of transcranial focused ultrasound simulations.

Objective. Low-intensity transcranial ultrasound stimulation (TUS) is a promising non-invasive brain stimulation (NIBS) technique. TUS can reach deeper areas and target smaller regions in the brain than other NIBS techniques, but its application in humans is hampered by the lack of a straightforward and reliable procedure to predict the induced ultrasound exposure. Here, we examined how skull modeling affects computer simulations of TUS.Approach. We characterized the ultrasonic beam after transmission through a sheep skull with a hydrophone and performed computed tomography (CT) image-based simulations of the experimental setup. To study the skull model's impact, we varied: CT acquisition parameters (tube voltage, dose, filter sharpness), image interpolation, segmentation parameters, acoustic property maps (speed-of-sound, density, attenuation), and transducer-position mismatches. We compared the impact of modeling parameter changes on model predictions and on measurement agreement. Spatial-peak intensity and location, total power, and the Gamma metric (a measure for distribution differences) were used as quantitative criteria. Modeling-based sensitivity analysis was also performed for two human head models.Main results. Sheep skull attenuation assignment and transducer positioning had the most important impact on spatial peak intensity (overestimation up to 300%, respectively 30%), followed by filter sharpness and tube voltage (up to 20%), requiring calibration of the mapping functions. Positioning and skull-heterogeneity-structure strongly affected the intensity distribution (gamma tolerances exceeded in>80%, respectively>150%, of the focus-volume in water), necessitating image-based personalized modeling. Simulation results in human models consistently demonstrate a high sensitivity to the skull-heterogeneity model, attenuation tuning, and transducer shifts, the magnitude of which depends on the underlying skull structure complexity.Significance. Our study reveals the importance of properly modeling the skull-heterogeneity and its structure and of accurately reproducing the transducer position. The results raise red flags when translating modeling approaches among clinical sites without proper standardization and/or recalibration of the imaging and modeling parameters.

Transcranial focused ultrasound stimulation with high spatial resolution.

BACKGROUND: Low-intensity transcranial focused ultrasound stimulation is a promising candidate for noninvasive brain stimulation and accurate targeting of brain circuits because of its focusing capability and long penetration depth. However, achieving a sufficiently high spatial resolution to target small animal sub-regions is still challenging, especially in the axial direction. OBJECTIVE: To achieve high axial resolution, we designed a dual-crossed transducer system that achieved high spatial resolution in the axial direction without complex microfabrication, beamforming circuitry, and signal processing. METHODS: High axial resolution was achieved by crossing two ultrasound beams of commercially available piezoelectric curved transducers at the focal length of each transducer. After implementation of the fixture for the dual-crossed transducer system, three sets of in vivo animal experiments were conducted to demonstrate high target specificity of ultrasound neuromodulation using the dual-crossed transducer system (n = 38). RESULTS: The full-width at half maximum (FWHM) focal volume of our dual-crossed transducer system was under 0.52 µm3. We report a focal diameter in both lateral and axial directions of 1 mm. To demonstrate successful in vivo brain stimulation of wild-type mice, we observed the movement of the forepaws. In addition, we targeted the habenula and verified the high spatial specificity of our dual-crossed transducer system. CONCLUSIONS: Our results demonstrate the ability of the dual-crossed transducer system to target highly specific regions of mice brains using ultrasound stimulation. The proposed system is a valuable tool to study the complex neurological circuitry of the brain noninvasively.

Miniature ultrasound ring array transducers for transcranial ultrasound neuromodulation of freely-moving small animals.

BACKGROUND: Current transcranial ultrasound stimulation for small animal in vivo experiment is limited to acute stimulation under anesthesia in stereotaxic fixation due to bulky and heavy curved transducers. METHODS: We developed a miniaturized ultrasound ring array transducer which is capable of invoking motor responses through neuromodulation of freely-moving awake mice. RESULTS: The developed transducer is a 32-element, 183-kHz ring array with a weight of 0.035 g (with PCB: 0.73 g), a diameter of 8.1 mm, a focal length of 2.3 mm, and lateral resolution of 2.75 mm. By developing an affixation scheme suitable for freely-moving animals, the transducer was successfully coupled to the mouse brain and induced motor responses in both affixed and awake states. CONCLUSION: Ultrasound neuromodulation of a freely-moving animal is now possible using the developed lightweight and compact system to conduct a versatile set of in vivo experiments.

Capacitive Micromachined Ultrasonic Transducer (CMUT) ring array for transcranial ultrasound neuromodulation.

Non-invasive brain stimulation of small animals plays an important role in neuroscience especially in understanding fundamental mechanisms of brain disorders. Here, we report a miniaturized ultrasound transducer array designed for non-invasive brain stimulation of mouse for the first time. We designed and fabricated a Capacitive Micromachined Ultrasonic Transducer (CMUT) ring array that operates at 183 kHz in immersion. The fabricated transducer ring array exhibited a focal length of 2.25 mm and a maximum intensity of 175 mW/cm2. Because the array was fabricated in a ring shape, a natural focus was achieved and thus, no additional focusing circuitries or acoustic lens were required. Thus, a compact packaging was achieved with minimum surgical procedures for in vivo mouse experiments. Using the developed micromachined transducer array and simple packaging, we successfully induced the motor responses of a mouse. The success rate of ultrasound stimulation was quantified by recording the electromyography (EMG) signal during the stimulation. While the current ultrasound neuromodulation system is limited to acute experiments, the presented light (< 1 g) and compact ultrasound neuromodulation system with a natural focus would enable chronic ultrasound neuromodulation experiments on freely-moving mice.

Improved Target Specificity of Transcranial Focused Ultrasound Stimulation (TFUS) using Double-Crossed Ultrasound Transducers.

Ultrasound neuromodulation is a promising stimulation modality because of its non-invasiveness, focusing and steering capability, and relatively high spatial resolution compared to the other stimulation modalities. However, despite the high lateral resolution, the ultrasound beam in the axial direction is relatively long, especially when compared to the small size of the mouse brain. Here, we report a new ultrasound focusing technique for small animal in vivo experiments where a high spatial resolution in both lateral and axial directions is achieved by crossing two ultrasound beams. The focal volume of a full width half maximum (FWHM) of our proposed system is only 0.161 mm3 and the focal diameter in the axial direction is about 1 mm, which is ten times smaller than the previously reported ultrasound neuromodulation system. Thus, the proposed system enables targeting a sub-region of a mouse brain using ultrasound for the first time. We also demonstrate successful stimulation of the motor cortex through in vivo mice experiments where the movement of forepaw of the mouse was observed using the double-crossed ultrasound transducers. Moreover, by sweeping the focal point in the z-axis and measuring the success rate of stimulated movements, we show that our double-transducer system targeted a region with 2 mmresolution in the dorsal-ventral (DV) coordinates. The success rate of the double-crossed ultrasound stimulation was quantified by recording the electromyography (EMG) signals during the stimulation. Our results show that the double-crossed ultrasound transducer system with a ten times higher spatial resolution enables highly specific and noninvasive stimulation of small animals and thus enables versatile in vivo experiments to study functional connectivities of brain circuits.