Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring.

Wrist-based respiratory rate (RR) measurement during sleep faces accuracy limitations. This study aimed to assess the accuracy of the RR estimation function during sleep based on the severity of obstructive sleep apnea (OSA) using the Samsung Galaxy Watch (GW) series. These watches are equipped with accelerometers and photoplethysmography sensors for RR estimation. A total of 195 participants visiting our sleep clinic underwent overnight polysomnography while wearing the GW, and the RR estimated by the GW was compared with the reference RR obtained from the nasal thermocouple. For all participants, the root mean squared error (RMSE) of the average overnight RR and continuous RR measurements were 1.13 bpm and 1.62 bpm, respectively, showing a small bias of 0.39 bpm and 0.37 bpm, respectively. The Bland-Altman plots indicated good agreement in the RR measurements for the normal, mild, and moderate OSA groups. In participants with normal-to-moderate OSA, both average overnight RR and continuous RR measurements achieved accuracy rates exceeding 90%. However, for patients with severe OSA, these accuracy rates decreased to 79.45% and 75.8%, respectively. The study demonstrates the GW's ability to accurately estimate RR during sleep, even though accuracy may be compromised in patients with severe OSA.

Performance evaluation of a wrist-worn reflectance pulse oximeter during sleep.

OBJECTIVES: To characterize and evaluate the estimation of oxygen saturation measured by a wrist-worn reflectance pulse oximeter during sleep. METHODS: Ninety-seven adults with sleep disturbances were enrolled. Oxygen saturation was simultaneously measured using a reflectance pulse oximeter (Galaxy Watch 4 [GW4], Samsung, South Korea) and a transmittance pulse oximeter (polysomnography) as a reference. The performance of the device was evaluated using the root mean squared error (RMSE) and coverage rate. Additionally, GW4-derived oxygen desaturation index (ODI) was compared with the apnea-hypopnea index (AHI) derived from polysomnography. RESULTS: The GW4 had an overall RMSE of 2.3% and negligible bias of -0.2%. A Bland-Altman density plot showed good agreement between the GW4 and the reference pulse oximeter. RMSEs were 1.65 ± 0.57%, 1.76 ± 0.65%, 1.93 ± 0.54%, and 2.93 ± 1.71% for normal (n = 18), mild (n = 21), moderate (n = 23), and severe obstructive sleep apnea (n = 35), respectively. The data rejection rate was 26.5%, which was caused by fluctuations in contact pressure and the discarding of data less than 70% of saturation. A GW4-ODI ≥5/h had the highest ability to predict AHI ≥15/h with sensitivity, specificity, accuracy, and area under the curve of 89.7%, 64.1%, 79.4%, and 0.908, respectively. CONCLUSIONS: This study evaluated the estimation of oxygen saturation by the GW4 during sleep. This device complies with both Food and Drug Administration and International Organization for Standardization standards. Further improvements in the algorithms of wearable devices are required to obtain more accurate and reliable information about oxygen saturation measurements.

Optical recording of neural responses to gold-nanorod mediated photothermal neural inhibition.

BACKGROUND: Photothermal stimulation is a heat-mediated neuromodulation technique. When photothermal effects are induced on neuronal membrane, it can either excite or inhibit neural spiking activities. It has been demonstrated that gold nanorod mediated photothermal stimulation could decrease the electrical activity of cultured neural network. We investigated the effect of photothermal inhibition on neural activity using calcium imaging technique. NEW METHOD: Hippocampal neurons were cultured on a gold-nanorod-coated-microelectrode array and near-infrared laser was illuminated to induce neural inhibition. The neuronal responses at a single-cell resolution were measured by an extracellular recording and calcium imaging simultaneously. RESULTS: The photothermal effect on neural spikes were confirmed by electrical recording and calcium imaging. The decrease in neural spikes in electrical recordings during NIR illumination was correlated with the neighboring neural activity quantified by calcium spikes. COMPARISON WITH EXISTING METHOD(S): Optical recording at the single cell resolution was attempted during photothermal stimulation to confirm the neural suppression effect. CONCLUSIONS: Heat mediated suppression of neural activity was optically validated in single cell level. The present study will be helpful to understand the emerging photothermal neuromodulation technology.

Coastal Waste Detection Based on Deep Convolutional Neural Networks.

Coastal waste not only has a seriously destructive effect on human life and marine ecosystems, but it also poses a long-term economic and environmental threat. To solve the issues of a poor manual coastal waste sorting environment, such as low sorting efficiency and heavy tasks, we develop a novel deep convolutional neural network by combining several strategies to realize intelligent waste recognition and classification based on the state-of-the-art Faster R-CNN framework. Firstly, to effectively detect small objects, we consider multiple-scale fusion to get rich semantic information from the shallower feature map. Secondly, RoI Align is introduced to solve positioning deviation caused by the regions of interest pooling. Moreover, it is necessary to correct key parameters and take on data augmentation to improve model performance. Besides, we create a new waste object dataset, named IST-Waste, which is made publicly to facilitate future research in this field. As a consequence, the experiment shows that the algorithm's mAP reaches 83%. Detection performance is significantly better than Faster R-CNN and SSD. Thus, the developed scheme achieves higher accuracy and better performance against the state-of-the-art alternative.

Addition of autogenous bone chips to deproteinized bovine bone mineral does not have additional benefit in lateral ridge augmentation-A preclinical in vivo experimental study.

OBJECTIVE: To compare the outcome after extensive lateral guided bone regeneration using deproteinized bovine bone mineral (DBBM) with or without autogenous bone chips in a canine model of chronic horizontal alveolar ridge defect. MATERIALS AND METHODS: The second, third and fourth lower premolars of both sides were extracted, and the buccal bone walls were completely removed in five beagle dogs. After 4 weeks, DBBM particles mixed with autogenous bone chips at a ratio of 1:1 were grafted at one side (DBBM/Auto group), while DBBM particles alone were grafted at the contralateral side (DBBM group). The graft materials on both sides were covered by a resorbable collagen membrane and fixation pins. Microcomputed tomographic volume and histomorphometric analyses were performed at 16 weeks post-surgery. RESULTS: The ridges of both groups were recovered horizontally, but new bone formation beyond the original ridge contour at the defect site was not found. The DBBM group exhibited a larger total radiographic augmented volume and new bone volume compared with the DBBM/Auto group, but the differences were minimal (p > .05). Histologically, the regenerated area and new bone area were also slightly larger without any statistical significance in the DBBM group than in the DBBM/Auto group (p > .05). CONCLUSION: The addition of autogenous bone chips to DBBM for lateral ridge augmentation may confer no advantage over grafting DBBM alone with respect to both space maintenance and de novo bone formation in dogs.

In-Situ Data-Driven Buffeting Response Analysis of a Cable-Stayed Bridge.

To analytically evaluate buffeting responses, the analysis of wind characteristics such as turbulence intensity, turbulence length, gust, and roughness coefficient must be a priority. The analytical buffeting response is affected by the static aerodynamic force coefficient, flutter coefficient, structural damping ratio, aerodynamic damping ratio, and natural frequencies of the bridge. The cable-stayed bridge of interest in this study has been used for 32 years. In that time, the terrain conditions around the bridge have markedly changed from the conditions when the bridge was built. Further, the wind environments have varied considerably due to climate change. For these reasons, the turbulence intensity, length, spectrum coefficient, and roughness coefficient of the bridge site must be evaluated from full-scale measurements using a structural health monitoring system. Although the bridge is located on a coastal area, the evaluation results indicated that the wind characteristics of bridge site were analogous to those of open terrain. The buffeting response of the bridge was analyzed using the damping ratios, static aerodynamic force coefficients, and natural frequencies obtained from measured data. The analysis was performed for four cases. Two case analyses were performed by applying the variables obtained from measured data, while two other case analyses were performed based on the Korean Society of Civil Engineers (KSCE) Design Guidelines for Steel Cable Supported Bridges. The calculated responses of each analysis case were compared with the buffeting response measured at wind speeds of less than 25 m/s. The responses obtained by numerical analysis using estimated variables based on full-scale measurements agreed well with the measured buffeting responses measured at wind speeds of less than 25 m/s. Moreover, an extreme wind speed of 44 m/s, corresponding to a recurrence interval of 200 years, was derived from the Gumbel distribution. Therefore, the buffeting responses at wind speeds of 45 m/s were also determined by applying the estimated variables. From these results, management criteria based on measurement data for in-service bridge are determined and each level of management is proposed.

Development of Sensor Registry System-Based Predictive Information Service Using a Grid.

A sensor registry system (SRS) registers sensor metadata and provides them for a seamless semantic process. Recently, network coverage information-based SRS (NC-SRS) was developed to provide sensor information filtering by combining path prediction and network coverage checks. However, the NC-SRS has problems caused by issues such as termination of OpenSignal service and pre-building road segments. Therefore, this paper proposes a sensor registry system-based predictive information service (SRS-PIS) using a grid. SRS-PIS predicts a path based on the grid, checks the network coverage, and filters the sensor. This paper presents a grid-based real-time path prediction algorithm and an algorithm for grouping network service-disabled areas. To obtain network coverage information, we constructed and implemented a grid-based coverage map through experiment to measure the signal strength. As an evaluation, we compared features among SRS-based systems and SRS-PIS, and compared advantages and disadvantages between segment-based and grid-based methods.

Recovery of early neural spikes from stimulation electrodes using a DC-coupled low gain high resolution data acquisition system.

BACKGROUND: Neural responses to electrical stimulation provide valuable information to probe and study the network function. Especially, recording neural responses from the stimulated site provides improved neural interfacing method. However, it is difficult to measure short-delayed responses at the stimulated electrode due to the saturation of the amplifier after stimulation which is called "stimulus artifact". Despite the advances in handling stimulation artifacts, it is still very challenging to deal with the artifacts if one tries to stimulate and record from the same electrode. NEW METHOD: In this paper, we developed a system consisting of 24 bit ADC and low gain DC-amplifier which allows us to record the entire responses including saturation-free stimulus artifact and neural responses with excellent resolution. RESULTS: Our approach showed saturation-free recording after stimulation, which makes it possible to recover neural spike as early as in 2 ms at the stimulating electrode with digital elimination methods. COMPARISON WITH EXISTING METHODS: With our system we could record neural signals after stimulation that was difficult with high gain and high pass filtered recording system due to amplifier saturation. CONCLUSIONS: Our new system can enhance interface performance with its higher robustness and with simple system configuration.

Inkjet-Printed Biofunctional Thermo-Plasmonic Interfaces for Patterned Neuromodulation.

Localized heat generation by the thermo-plasmonic effect of metal nanoparticles has great potential in biomedical engineering research. Precise patterning of the nanoparticles using inkjet printing can enable the application of the thermo-plasmonic effect in a well-controlled way (shape and intensity). However, a universally applicable inkjet printing process that allows good control in patterning and assembly of nanoparticles with good biocompatibility is missing. Here we developed inkjet-printing-based biofunctional thermo-plasmonic interfaces that can modulate biological activities. We found that inkjet printing of plasmonic nanoparticles on a polyelectrolyte layer-by-layer substrate coating enables high-quality, biocompatible thermo-plasmonic interfaces across various substrates (rigid/flexible, hydrophobic/hydrophilic) by induced contact line pinning and electrostatically assisted nanoparticle assembly. We experimentally confirmed that the generated heat from the inkjet-printed thermo-plasmonic patterns can be applied in micrometer resolution over a large area. Lastly, we demonstrated that the patterned thermo-plasmonic effect from the inkjet-printed gold nanorods can selectively modulate neuronal network activities. This inkjet printing process therefore can be a universal method for biofunctional thermo-plasmonic interfaces in various bioengineering applications.

Gold nanostar-mediated neural activity control using plasmonic photothermal effects.

Nanomaterials have emerged as an essential tool for the understanding of cellular level mechanism in the fields of biology and medical science. Recently, researchers have been studying the regulation of neuronal activity using plasmonic nanoparticles and light, and it has been reported that photothermal effects could lead to both excitation and inhibition of neuronal cells. So far, only a few photothermal transducers have been applied to modulate neural activity. In this paper, we synthesized biocompatible gold nanostars (AuNSs) which generate heat by absorbing near-infrared (NIR) light. And we used the AuNS to inhibit the activity of neurons through light stimulation. We have demonstrated that AuNS inhibits the neural activity by NIR laser in both chip-attached mode and cell-attached mode. We also confirmed the suppression of single neuron signal by using digital micromirror device (DMD) set up. This approach is possible to inhibit the neural firing by controlling the intensity of light, and overcome the disadvantages of conventional electrochemical stimulation methods. This method of NIR-mediated stimulating neurons using light sensitive AuNS will be a powerful tool for neuromodulation researches and neuroscience studies.

Digital micromirror based near-infrared illumination system for plasmonic photothermal neuromodulation.

Light-mediated neuromodulation techniques provide great advantages to investigate neuroscience due to its high spatial and temporal resolution. To generate a spatial pattern of neural activity, it is necessary to develop a system for patterned-light illumination to a specific area. Digital micromirror device (DMD) based patterned illumination system have been used for neuromodulation due to its simple configuration and design flexibility. In this paper, we developed a patterned near-infrared (NIR) illumination system for region specific photothermal manipulation of neural activity using NIR-sensitive plasmonic gold nanorods (GNRs). The proposed system had high power transmission efficiency for delivering power density up to 19 W/mm2. We used a GNR-coated microelectrode array (MEA) to perform biological experiments using E18 rat hippocampal neurons and showed that it was possible to inhibit neural spiking activity of specific area in neural circuits with the patterned NIR illumination. This patterned NIR illumination system can serve as a promising neuromodulation tool to investigate neuroscience in a wide range of physiological and clinical applications.

Comparison of efficiency of elastic and non-elastic taping on induced quadriceps fatigue by knee extension exercise.

[Purpose] The purpose of this study is to examine the effects of elastic and non-elastic taping on induced quadriceps fatigue by knee extension exercise. [Subjects and Methods] Thirty healthy females were randomly assigned to an elastic tape group (ET, n=10), a non-elastic tape group (NET, n=10), or a no tape group (NT, n=10). Taping groups attached taping on quadriceps femoris. Three groups are conducted knee extension exercise for 10 times and 3 sets during 10 minutes. Knee extension peak torque measured before and after knee extension exercise. One-way analysis of variance was used to assess the statistical significance of knee extension peak torque. [Results] No significant difference in changes in maximum muscle strength per unit weight from before to after the muscle fatigue exercise was found in the ET, NET, or NT groups (12.1 ± 4.2, 11.7 ± 7.1, and 6.7 ± 3.4 N/kg, respectively). [Conclusion] Taping facilitated muscle performance, but it also increased susceptibility to fatigue resulting from greater muscle activation.

A Network Coverage Information-Based Sensor Registry System for IoT Environments.

The Internet of Things (IoT) is expected to provide better services through the interaction of physical objects via the Internet. However, its limitations cause an interoperability problem when the sensed data are exchanged between the sensor nodes in wireless sensor networks (WSNs), which constitute the core infrastructure of the IoT. To address this problem, a Sensor Registry System (SRS) is used. By using a SRS, the information of the heterogeneous sensed data remains pure. If users move along a road, their mobile devices predict their next positions and obtain the sensed data for that position from the SRS. If the WSNs in the location in which the users move are unstable, the sensed data will be lost. Consider a situation where the user passes through dangerous areas. If the user's mobile device cannot receive information, they cannot be warned about the dangerous situation. To avoid this, two novel SRSs that use network coverage information have been proposed: one uses OpenSignal and the other uses the probabilistic distribution of the users accessing SRS. The empirical study showed that the proposed method can seamlessly provide services related to sensing data under any abnormal circumstance.