Real-time monitoring of cortical brain activity in response to acute pain using wide-area Ca2+ imaging.

Previous human and rodent studies indicated that nociceptive stimuli activate many brain regions that is involved in the somatosensory and emotional sensation. Although these studies have identified several important brain regions involved in pain perception, it has been a challenge to observe neural activity directly and simultaneously in these multiple brain regions during pain perception. Using a transgenic mouse expressing G-CaMP7 in majority of astrocytes and a subpopulation of excitatory neurons, we recorded the brain activity in the mouse cerebral cortex during acute pain stimulation. Both of hind paw pinch and intraplantar administration of formalin caused strong transient increase of the fluorescence in several cortical regions, including primary somatosensory, motor and retrosplenial cortex. This increase of the fluorescence intensity was attenuated by the pretreatment with morphine. The present study provides important insight into the cortico-cortical network during pain perception.

Investigating the Modulation of the VTA Neurons in Nicotine-Exposed Pups during Early Maturation Using Optogenetics.

Advancing the understanding of the relationship between perinatal nicotine addiction and the reward mechanism of the brain is crucial for uncovering and implementing new treatments for addiction control and prevention. The mesolimbic pathway of the brain, also known as the reward pathway, consists of two main areas that regulate dopamine (DA) and addiction-related behaviors. The ventral tegmental area (VTA) releases DA when stimulated, causing the propagation of neuronal firing along the pathway. This ends in the release of DA into the extracellular space of the nucleus accumbens (NAc), which is directly modulated by the uptake of DA. Much research has been conducted on the effects of nicotine addiction, but little research has been conducted concerning nicotine addiction and the mesolimbic pathway regarding maturation due to the small brain size. In this study, we apply our novel microstimulation experimental system to rat pups that have been perinatally exposed to nicotine. By using our self-fabricated photo-stimulation (PS) device, we can stimulate the VTA and collect dialysate, which is then used to estimate DA released into the NAc. The proposed platform has demonstrated the potential to monitor neural pathways as the pups mature.

Investigating the Influence of Morphine and Cocaine on the Mesolimbic Pathway Using a Novel Microimaging Platform.

Dopamine (DA)'s relationship with addiction is complex, and the related pathways in the mesocorticolimbic system are used to deliver DA, regulating both behavioral and perceptual actions. Specifically, the mesolimbic pathway connecting the ventral tegmental area (VTA) and the nucleus accumbens (NAc) is crucial in regulating memory, emotion, motivation, and behavior due to its responsibility to modulate dopamine. To better investigate the relationship between DA and addiction, more advanced mapping methods are necessary to monitor its production and propagation accurately and efficiently. In this study, we incorporate dLight1.2 adeno-associated virus (AAV) into our latest CMOS (complementary metal-oxide semiconductor) imaging platform to investigate the effects of two pharmacological substances, morphine and cocaine, in the NAc using adult mice. By implanting our self-fabricated CMOS imaging device into the deep brain, fluorescence imaging of the NAc using the dLight1.2 AAV allows for the visualization of DA molecules delivered from the VTA in real time. Our results suggest that changes in extracellular DA can be observed with this adapted system, showing potential for new applications and methods for approaching addiction studies. Additionally, we can identify the unique characteristic trend of DA release for both morphine and cocaine, further validating the underlying biochemical mechanisms used to modulate dopaminergic activation.

Multi-Region Microdialysis Imaging Platform Revealed Dorsal Raphe Nucleus Calcium Signaling and Serotonin Dynamics during Nociceptive Pain.

In this research, we combined our ultralight micro-imaging device for calcium imaging with microdialysis to simultaneously visualize neural activity in the dorsal raphe nucleus (DRN) and measure serotonin release in the central nucleus of the amygdala (CeA) and the anterior cingulate cortex (ACC). Using this platform, we observed brain activity following nociception induced by formalin injection in the mouse's hind paw. Our device showed that DRN fluorescence intensity increased after formalin injection, and the increase was highly correlated with the elevation in serotonin release in both the CeA and ACC. The increase in calcium fluorescence intensity occurred during the acute and inflammatory phases, which suggests the biphasic response of nociceptive pain. Furthermore, we found that the increase in fluorescence intensity was positively correlated with mouse licking behavior. Lastly, we compared the laterality of pain stimulation and found that DRN fluorescence activity was higher for contralateral stimulation. Microdialysis showed that CeA serotonin concentration increased only after contralateral stimulation, while ACC serotonin release responded bilaterally. In conclusion, our study not only revealed the inter-regional serotonergic connection among the DRN, the CeA, and the ACC, but also demonstrated that our device is feasible for multi-site implantation in conjunction with a microdialysis system, allowing the simultaneous multi-modal observation of different regions in the brain.

Investigating the Influence of GABA Neurons on Dopamine Neurons in the Ventral Tegmental Area Using Optogenetic Techniques.

Dopamine (DA) is the key regulator of reward behavior. The DA neurons in the ventral tegmental area (VTA) and their projection areas, which include the prefrontal cortex (PFC), nucleus accumbens (NAc), and amygdala, play a primary role in the process of reward-driven behavior induced by the drugs of addiction, including nicotine and alcohol. In our previous study, we developed a novel platform consisting of micro-LED array devices to stimulate a large area of the brain of rats and monkeys with photo-stimulation and a microdialysis probe to estimate the DA release in the PFC. Our results suggested that the platform was able to detect the increased level of dopamine in the PFC in response to the photo-stimulation of both the PFC and VTA. In this study, we used this platform to photo-stimulate the VTA neurons in both ChrimsonR-expressing (non-specific) wild and dopamine transporter (DAT)-Cre (dopamine specific) mice, and measured the dopamine release in the nucleus accumbens shell (NAcShell). We measured the DA release in the NAcShell in response to optogenetic stimulation of the VTA neurons and investigated the effect of GABAergic neurons on dopaminergic neurons by histochemical studies. Comparing the photo-stimulation frequency of 2 Hz with that of 20 Hz, the change in DA concentration at the NAcShell was greater at 20 Hz in both cases. When ChrimsonR was expressed specifically for DA, the release of DA at the NAcShell increased in response to photo-stimulation of the VTA. In contrast, when ChrimsonR was expressed non-specifically, the amount of DA released was almost unchanged upon photo-stimulation. However, for nonspecifically expressed ChrimsonR, intraperitoneal injection of bicuculline, a competitive antagonist at the GABA-binding site of the GABAA receptor, also significantly increased the release of DA at the NAcShell in response to photo-stimulation of the VTA. The results of immunochemical staining confirm that GABAergic neurons in the VTA suppress DA activation, and also indicate that alterations in GABAergic neurons may have serious downstream effects on DA activity, NAcShell release, and neural adaptation of the VTA. This study also confirms that optogenetics technology is crucial to study the relationship between the mesolimbic dopaminergic and GABAergic neurons in a neural-specific manner.

Astrocytes Decreased the Sensitivity of Glioblastoma Cells to Temozolomide and Bay 11-7082.

Glioblastoma multiforme (GBM) is the most common malignant type of astrocytic tumors. GBM patients have a poor prognosis with a median survival of approximately 15 months despite the "Stupp" Regimen and high tumor recurrence due to the tumor resistance to chemotherapy. In this study, we co-cultured GBM cells with human astrocytes in three-dimensional (3D) poly(ethylene glycol) dimethyl acrylate (PEGDA) microwells to mimic the tumor microenvironment. We treated 3D co- and mono-cultured cells with Temozolomide (TMZ) and the nuclear factor-κB (NF-κB) inhibitor Bay 11-7082 and investigated the combined effect of the drugs. We assessed the expressions of glial fibrillary acidic protein (GFAP) and vimentin that play a role in the tumor malignancy and activation of the astrocytes as well as Notch-1 and survivin that play a role in GBM malignancy after the drug treatment to understand how astrocytes induced GBM drug response. Our results showed that in the co-culture, astrocytes increased GBM survival and resistance after combined drug treatment compared to mono-cultures. These data restated the importance of 3D cell culture to mimic the tumor microenvironment for drug screening.

Nicotine exposure increases the complexity of dopamine neurons in the parainterfascicular nucleus (PIF) sub-region of VTA.

BACKGROUND: Recent publications highlight differences within the sub-regions of the ventral tegmental area (VTA) including the parabrachial pigmented nucleus (PBP), parainterfascicular nucleus (PIF) and paranigral nucleus (PN) in the projections to the prefrontal cortex (PFC) and the glutamatergic pathway. METHODS: In order to characterize the effects of prenatal nicotine exposure on the mesocorticolimbic system of the rat offspring, local field potentials were recorded from 27 sites across the VTA of 9 rats aged 40-55 days. The extracellular VTA neural activities were analyzed using Approximate Entropy (ApEn) method. Approximate entropy values were then grouped according to each anatomic location including the PBP, PIF and PN. RESULTS: Our results have shown that the local field potentials corresponding to the neurons located in the PIF region of the VTA have ApEn values significantly higher (p = 2x10-4) in the maternal nicotine cases when compared to the saline. CONCLUSION: Therefore, we speculate that the dopamine neurons located in the PIF sub-region of the VTA are very likely involved with the nicotine addiction.

Lightweight Neural Network for Sleep Posture Classification Using Pressure Sensing Mat at Various Sensor Densities.

Recently, pressure-sensing mats have been widely used to capture static and dynamic pressure over sleep for posture recognition. Both a full-size mat with a low-density sensing array for figuring out the structure of the whole body and a miniature scale mat with a high-density sensing array for identifying the local characteristics around the chest have been investigated. However, both of the mat systems may face the challenge in the trade-off between the computational complexity (involving the size, density, etc. of the mat) and the performance of sleep posture recognition, where high performance may requires overcomplex computation and result in time latency in real-time sleep posture monitoring. In this paper, a lightweight neural network named ConcatNet, is proposed to realize sleep postures (supine, left, right, and prone) recognition in real time while maintaining a favorable performance. In ConcatNet, the inception module is proposed to extract the image features under multiple receptive fields, while the multi-layer feature fusion module is utilized to fuse deep and shallow features to enhance the model performance. To further improve the efficiency of the model, the depthwise convolution is adopoted. ConcatNet models in 3 different scales (ConcatNet-S, ConcatNet-M, and ConcatNet-L) are built to explore the impact of the sensor density on sleep posture recognition performance. Experimental results exhibit that ConcatNet-M corresponding to medium sensor density ( 16×16 ) achieved the best comprehensive performance, with short-term data cross-validation accuracy at 95.56% and overnight data testing accuracy at 94.68%. The model size is 7.91KB, FLOPs is 56.47K, and the inference time is only 0.38ms, which shows an outstanding performance of real-time sleep posture recognition with minimum consumption, indicating the potential to be deployed in mobile devices.

Oculometric biomarkers of visuomotor deficits in clinically asymptomatic patients with systemic lupus erythematosus undergoing long-term hydroxychloroquine treatment.

Introduction: This study examines a set of oculomotor measurements, or "oculometric" biomarkers, as potential early indicators of visual and visuomotor deficits due to retinal toxicity in asymptomatic Systemic Lupus Erythematosus (SLE) patients on long-term hydroxychloroquine (HCQ) treatment. The aim is to identify subclinical functional impairments that are otherwise undetectable by standard clinical tests and to link them to structural retinal changes. Methods: We measured oculomotor responses in a cohort of SLE patients on chronic HCQ therapy using a previously established behavioral task and analysis technique. We also examined the relationship between oculometrics, OCT measures of retinal thickness, and standard clinical perimetry measures of visual function in our patient group using Bivariate Pearson Correlation and a Linear Mixed-Effects Model (LMM). Results: Significant visual and visuomotor deficits were found in 12 asymptomatic SLE patients on long-term HCQ therapy compared to a cohort of 17 age-matched healthy controls. Notably, six oculometrics were significantly different. The median initial pursuit acceleration was 22%, steady-state pursuit gain 16%, proportion smooth 7%, and target speed responsiveness 31% lower, while catch-up saccade amplitude was 46% and fixation error 46% larger. Excluding the two patients with diagnosed mild toxicity, four oculometrics, all but fixation error and proportion smooth, remained significantly impaired compared to controls. Across our population of 12 patients (24 retinae), we found that pursuit latency, initial acceleration, steady-state gain, and fixation error were linearly related to retinal thickness even when age was accounted for, while standard measures of clinical function (Mean Deviation and Pattern Standard Deviation) were not. Discussion: Our data show that specific oculometrics are sensitive early biomarkers of functional deficits in SLE patients on HCQ that could be harnessed to assist in the early detection of HCQ-induced retinal toxicity and other visual pathologies, potentially providing early diagnostic value beyond standard visual field and OCT evaluations.

Grand Challenges at the Interface of Engineering and Medicine.

Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution is now equipped at varying degrees of sophistication with the ability to monitor human health in both non-invasive and invasive modes. The multiple scales at which human physiology can be interrogated provide a profound perspective on health and disease. We are at the nexus of creating "avatars" (herein defined as an extension of "digital twins") of human patho/physiology to serve as paradigms for interrogation and potential intervention. Motivated by the emergence of these new capabilities, the IEEE Engineering in Medicine and Biology Society, the Departments of Biomedical Engineering at Johns Hopkins University and Bioengineering at University of California at San Diego sponsored an interdisciplinary workshop to define the grand challenges that face biomedical engineering and the mechanisms to address these challenges. The Workshop identified five grand challenges with cross-cutting themes and provided a roadmap for new technologies, identified new training needs, and defined the types of interdisciplinary teams needed for addressing these challenges. The themes presented in this paper include: 1) accumedicine through creation of avatars of cells, tissues, organs and whole human; 2) development of smart and responsive devices for human function augmentation; 3) exocortical technologies to understand brain function and treat neuropathologies; 4) the development of approaches to harness the human immune system for health and wellness; and 5) new strategies to engineer genomes and cells.

Coronary calcium quantification using contrast-enhanced dual-energy computed tomography scans.

The purpose of this study is to evaluate a direct measure of calcium burden by using dual-energy computed tomography (DECT) during contrast-enhanced coronary imaging, potentially eliminating the need for an extra noncontrast X-ray acquisition. The ambiguity of separation of calcium from contrast material on contrast-enhanced images was solved by using virtual noncontrast images obtained by DECT. A new threshold CT number was required to detect the calcium carrying potential risk for adverse coronary events on virtual noncontrast images. Two methods were investigated to determine the 130 HU threshold for DECT scoring. An in vitro anthropomorphic phantom with 29 excised patient calcium plaques inserted was used for both a linear and a logistic regression analysis. An IRB approved in vivo prospective study of six patients was also performed to be used for logistic regression analysis. The threshold found by logistic regression model to define the calcium burden on virtual noncontrast images detects the calcium carrying potential risk for adverse coronary events correctly (2.45% error rate). DECT calcium mass and volume scores obtained by using the threshold correlates with both conventional Agatston and volume scores (r = 0.98, p < 0.001). A conventional CT cardiac exam requires two scans, including a noncontrast scan for calcium quantification and a contrast-enhanced scan for coronary angiography. With the ability to quantify calcium on DECT contrast-enhanced images, a DECT cardiac exam could be accomplished with one contrast-enhanced scan for both calcium quantification and coronary angiography. 

Targeted Sensitization of Glioblastoma Multiforme Using AAAPT Technology.

Glioblastoma Multiforme (GBM) is the most malignant type of all brain tumors. Current GBM treatment options include surgery, followed by radiation and chemotherapy. However, GBM can become resistant to therapy, resulting in tumor recurrence. GBM cells develop resistance to treatments by either downregulating cell death pathways (CD95) or upregulating cell survival pathways (NF-κB (p65)). Healthy tissues can be affected by the increased therapeutic dose. Therefore, it is important to develop a method that can only target GBM tumor cells, thereby reducing the non-specific uptake which will reduce the side effects. Here we demonstrate an application of novel priori activation of apoptosis pathways of tumor technology (AAAPT), which has been used to demonstrate the effect of targeted tumor sensitizers to make chemotherapy work at lower doses in breast, lung and prostate cancers. Treatment of GBM spheroids with AAAPT in 3D PEGDA microwells, showed an increase in cell death, an upregulation of cell death pathways, and a downregulation of cell survival pathways, in comparison to Temozolomide (TMZ), an oral alkylating agent, which is a commonly used chemotherapy in the treatment of GBM. The dose of AAAPT sensitizers may provide a promising method to increase treatment efficacy and reduce off-target toxicity, as an alternative to existing methods which cause significant off-target damage.

Prenatal nicotine exposure alters gene expression profiles of neurons in the sub-regions of the VTA during early postnatal development.

Brain growth occurs during the first 2 weeks of postnatal development in rats. This developmental period is equivalent to the third trimester of human gestation. Dendritic arborization, axonal growth, and gliogenesis are observed along with a strong maturation of neurotransmission during this critical development period. Furthermore, nicotine exposure during early development causes deficiencies in sensory and cognitive processing in adults. In this study, we further investigated the gene expression of neuron groups and the influence of perinatal nicotine exposure on gene expressions of neurons within the sub-regions of the ventral tegmental area (VTA) in 1 week, 2 week and 3-week-old rat pups. We exposed pregnant rats to nicotine perinatally on gestational day 7 through postnatal day 14. Pups are exposed to nicotine during pregnancy and through breastfeeding to investigate its effect in rat pups during early neuronal development. Real time PCR was used to find the relative expressions of gamma-aminobutyric acid (GABA), dopamine, and glutamate neuron markers within the three sub-regions of the VTA including the parabrachial pigmented nucleus (PBP), parainterfascicular (PIF), and paranigral nucleus (PN). Our results indicated that during early maturation, the dopamine marker tyrosine hydroxylase (TH) showed a consistently increased significance in PN sub-region compared to PIF and PBP. These results suggest that following perinatal nicotine exposure, VTA dopamine neurons, especially within the PN sub-region, are significantly excited starting from birth.

Processes for Designing Innovative Biomedical Hardware to Use in Space and on Earth.

The new era of space exploration is increasing the astronaut's number and diversity in low orbit and beyond. The influx of such a diverse crew population will also increase the need for medical technologies to ensure safe and productive missions. Such a need represents a unique opportunity to innovate and develop diagnostics and treatment tools to meet future needs. Historically, terrestrial regulatory oversight of biomedical design processes was considered separate from spaceflight regulatory processes because it did not address spaceflight constraints. These constraints challenge the creative development of unique solutions for use in space. Translation between healthcare innovation in spaceflight to healthcare on Earth and vice versa requires understanding the commonalities, unique needs and constraints. This manuscript provides a framework for comparing Earth-space design processes and a perspective on the best practices to improve healthcare equity and health outcomes.

New Horizons: From Vision to Impact.

Over the past two years, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated coronavirus disease (COVID-19), have greatly impacted our lives. This pandemic has revealed how our health care systems were not prepared for this major challenge, especially with respect to treatment, rapid diagnosis, and tracking, as well as limited hospital equipment, staff members, and resources. COVID-19 will be one of the deadliest pandemics in modern history and continues to strain resources available not only to health care workers, but also the general public, while the number of infected people and cases continues to drastically increase daily, especially within the United States and Europe.

Investigating miRNA-mRNA Interactions and Gene Regulatory Networks From VTA Dopaminergic Neurons Following Perinatal Nicotine and Alcohol Exposure Using Bayesian Network Analysis.

MicroRNAs play an important role in gene regulation for many biological systems, including nicotine and alcohol addiction. However, the underlying mechanism behind miRNAs and mRNA interaction is not well characterized. Microarrays are commonly used to quantify the expression levels of mRNAs and/or miRNAs simultaneously. In this study, we performed a Bayesian network analysis to identify mRNA and miRNA interactions following perinatal exposure to nicotine and/or alcohol. We utilized three sets of microarray data to predict the regulation relationship between mRNA and miRNAs. Following perinatal alcohol exposure, we identified two miRNAs: miR-542-5p and miR-874-3p, that exhibited a strong mutual influence on several mRNA in gene regulatory pathways, mainly Axon guidance and Dopaminergic synapses. Finally, we confirmed our predicted addiction pathways based on the Bayesian network analysis with the widely used Kyoto Encyclopedia of Genes and Genomes (KEGG)-based database and identified comparable relevant miRNA-mRNA pairs. We believe the Bayesian network can provide insight into the complexity biological process related to addiction and can potentially be applied to other diseases.

Cancelable HD-SEMG Biometric Identification via Deep Feature Learning.

Conventional biometric modalities, such as the face, fingerprint, and iris, are vulnerable against imitation and circumvention. Accordingly, secure biometric modalities with cancelable properties are needed for personal identification, especially in smart healthcare applications. Here we developed a person identification model using high-density surface electromyography (HD-sEMG) as biometric traits. In this model, the HD-sEMG biometric templates are cancelable and could be customized by the users through finger isometric contractions. A deep feature learning approach, implemented by convolutional neural networks (CNNs) is used to capture user-specific patterns from HD-sEMG signals and make identification decisions. This model has been validated on twenty-two subjects, with training and testing data acquired from two different days. The rank-1 identification accuracy and equal error rate for 44 identities (22 subjects × 2 accounts) can reach 87.23% and 4.66%, respectively. The cross-day identification accuracy of the proposed model is higher than the results of previous methods reported in the literature. The usability and efficiency of the proposed model are also investigated, indicating its potentials for practical applications.

Predicting Feeding Conditions of Premature Infants Through Non-Nutritive Sucking Skills Using a Sensitized Pacifier.

Due to the lack of enough physical or suck central pattern generator (SCPG) development, premature infants require assistance in improving their sucking skills as one of the first coordinated muscular activities in infants. Hence, we need to quantitatively measure their sucking abilities for future studies on their sucking interventions. Here, we present a new device that can measure both intraoral pressure (IP) and expression pressure (EP) as ororhithmic behavior parameters of non-nutritive sucking skills in infants. Our device is low-cost, easy-to-use, and accurate, which makes it appropriate for extensive studies. To showcase one of the applications of our device, we collected weekly data from 137 premature infants from 29 week-old to 36 week-old. Around half of the infants in our study needed intensive care even after they were 36 week-old. We call them full attainment of oral feeding (FAOF) infants. We then used the Non-nutritive sucking (NNS) features of EP and IP signals of infants recorded by our device to predict FAOF infants' sucking conditions. We found that our pipeline can predict FAOF infants several weeks before discharge from the hospital. Thus, this application of our device presents a robust and inexpensive alternative to monitor oral feeding ability in premature infants.

Healthcare Innovations to Address the Challenges of the COVID-19 Pandemic.

We have been faced with an unprecedented challenge in combating the COVID-19/SARS-CoV2 outbreak that is threatening the fabric of our civilization, causing catastrophic human losses and a tremendous economic burden globally. During this difficult time, there has been an urgent need for biomedical engineers, clinicians, and healthcare industry leaders to work together to develop novel diagnostics and treatments to fight the pandemic including the development of portable, rapidly deployable, and affordable diagnostic testing kits, personal protective equipment, mechanical ventilators, vaccines, and data analysis and modeling tools. In this position paper, we address the urgent need to bring these inventions into clinical practices. This paper highlights and summarizes the discussions and new technologies in COVID-19 healthcare, screening, tracing, and treatment-related presentations made at the IEEE EMBS Public Forum on COVID-19. The paper also provides recent studies, statistics and data and new perspectives on ongoing and future challenges pertaining to the COVID-19 pandemic.

Automatic Upper-Limb Brunnstrom Recovery Stage Evaluation via Daily Activity Monitoring.

Motor function assessment is crucial for post-stroke rehabilitation. Conventional evaluation methods are subjective, heavily depending on the experience of therapists. In light of the strong correlation between the stroke severity level and the performance of activities of daily living (ADLs), we explored the possibility of automatically evaluating the upper-limb Brunnstrom Recovery Stage (BRS) via three typical ADLs (tooth brushing, face washing and drinking). Multimodal data (acceleration, angular velocity, surface electromyography) were synchronously collected from 5 upper-limb-worn sensor modules. The performance of BRS evaluation system is known to be variable with different system parameters (e.g., number of sensor modules, feature types and classifiers). We systematically searched for the optimal parameters from different data segmentation strategies (five window lengths and four overlaps), 42 types of features, 12 feature optimization techniques and 9 classifiers with the leave-one-subject-out cross-validation. To achieve reliable and low-cost monitoring, we further explored whether it was possible to obtain a satisfactory result using a relatively small number of sensor modules. As a result, the proposed approach can correctly recognize the stages of all 27 participants using only three sensor modules with the optimized data segmentation parameters (window length: 7s, overlap: 50%), extracted features (simple square integral, slope sign change, modified mean absolute value 1 and modified mean absolute value 2), the feature optimization method (principal component analysis) and the logistic regression classifier. According to the literature, this is the first study to comprehensively optimize sensor configuration and parameters in each stage of the BRS classification framework. The proposed approach can serve as a factor-screening tool towards the automatic BRS classification and is promising to be further used at home.