Searchable Blockchain-Based Healthcare Information Exchange System to Enhance Privacy Preserving and Data Usability.

Ensuring the security and usability of electronic health records (EHRs) is important in health information exchange (HIE) systems that handle healthcare records. This study addressed the need to balance privacy preserving and data usability in blockchain-based HIE systems. We propose a searchable blockchain-based HIE system that enhances privacy preserving while improving data usability. The proposed methodology includes users collecting healthcare information (HI) from various Internet of Medical Things (IoMT) devices and compiling this information into EHR blocks for sharing on a blockchain network. This approach allows participants to search and utilize specific health data within the blockchain effectively. The results demonstrate that the proposed system mitigates the issues of traditional HIE systems by providing secure and user-friendly access to EHRs. The proposed searchable blockchain-based HIE system resolves the trade-off dilemma in HIE by achieving a balance between security and the data usability of EHRs.

Development of a Targeted SN-38-Conjugate for the Treatment of Glioblastoma.

Glioblastoma (GBM) is the most aggressive and fatal brain tumor, with approximately 10,000 people diagnosed every year in the United States alone. The typical survival period for individuals with glioblastoma ranges from 12 to 18 months, with significant recurrence rates. Common therapeutic modalities for brain tumors are chemotherapy and radiotherapy. The main challenges with chemotherapy for the treatment of glioblastoma are high toxicity, poor selectivity, and limited accumulation of therapeutic anticancer agents in brain tumors as a result of the presence of the blood-brain barrier. To overcome these challenges, researchers have explored strategies involving the combination of targeting peptides possessing a specific affinity for overexpressed cell-surface receptors with conventional chemotherapy agents via the prodrug approach. This approach results in the creation of peptide drug conjugates (PDCs), which facilitate traversal across the blood-brain barrier (BBB), enable preferential accumulation of chemotherapy within the neoplastic microenvironment, and selectively target cancerous cells. This approach increases accumulation in tumors, thereby improving therapeutic efficiency and minimizing toxicity. Leveraging the affinity of the HAIYPRH (T7) peptide for the transferrin receptor (TfR) overexpressed on the blood-brain barrier and glioma cells, a novel T7-SN-38 peptide drug conjugate was developed. The T7-SN-38 peptide drug conjugate demonstrates about a 2-fold reduction in glide score (binding affinity) compared to T7 while maintaining a comparable orientation within the TfR target site using Schrödinger-2022-3 Maestro 13.3 for ligand preparation and Glide SP-Peptide docking. Additionally, SN-38 extends into a solvent-accessible region, enhancing its susceptibility to protease hydrolysis at the cathepsin B (Cat B) cleavable site. The SN-38-ether-peptide drug conjugate displayed high stability in buffer at physiological pH, and cleavage of the conjugate to release free cytotoxic SN-38 was observed in the presence of exogenous cathepsin B. The synthesized peptide drug conjugate exhibited potent cytotoxic activities in cellular models of glioblastoma in vitro. In addition, blocking transferrin receptors using the free T7 peptide resulted in a notable inhibition of cytotoxicity of the conjugate, which was reversed when exogenous cathepsin B was added to cells. This work demonstrates the potential for targeted drug delivery to the brain in the treatment of glioblastoma using the transferrin receptor-targeted T7-SN-38 conjugate.

Kilohertz-frequency interferential current induces hypoalgesic effects more comfortably than TENS.

Recent research on transcutaneous electrical stimulation has shown that inhibiting nerve conduction with a kilohertz frequency is both effective and safe. This study primarily aims to demonstrate the hypoalgesic effect on the tibial nerve using transcutaneous interferential-current nerve inhibition (TINI), which injects the kilohertz frequency produced by the interferential currents. Additionally, the secondary objective was to compare the analgesic effect and comfort of TINI and transcutaneous electrical nerve stimulation (TENS). Thirty-one healthy adults participated in this cross-over repeated measures study. The washout period was set to 24 h or more. Stimulus intensity was set just below the pain threshold level. TINI and TENS were applied for 20 min each. The ankle passive dorsiflexion range of motion, pressure pain threshold (PPT), and tactile threshold were measured at the baseline, pre-test, test (immediately before ceasing intervention), and post-test (30 min after ceasing intervention) sessions. After the interventions, the participants evaluated the level of discomfort for TINI and TENS on a 10 cm visual analog scale (VAS). As the results, PPT significantly increased compared to baseline in test and posttest sessions of TINI, but not in those of TENS. Also, participants reported that TENS was 36% more discomfort than TINI. The hypoalgesic effect was not significantly different between TINI and TENS. In conclusion, we found that TINI inhibited mechanical pain sensitivity and that the inhibitory effect persisted long after electrical stimulation ceased. Our study also shows that TINI provides the hypoalgesic effect more comfortably than TENS.

Combining transcutaneous interferential-current for nerve inhibition with a robotic assistant device for increasing ankle dorsiflexion in walking.

BACKGROUND: A kilohertz-frequency alternating current transcutaneously applied was introduced as a novel neuromodulation technology for nerve inhibition innervating antagonist muscles. Combining this electrical nerve inhibition with a robotic assistance device has been proposed but not investigated. RESEARCH QUESTION: This study aimed to demonstrate the effect of combining electrical nerve inhibition with a wearable robotic device on increasing ankle dorsiflexion during walking. We hypothesized that the wearable robotic device would elicit a greater ankle dorsiflexion angle with the same force in walking by applying the transcutaneous interferential-current nerve inhibition (TINI) technique to the tibial nerve. METHODS: Eleven healthy young adults performed three experimental conditions. The ankle assistance (AA) condition was walking while wearing an ankle device with operating dorsiflexion assistance during pre-swing and swing phases. For the ankle assistance with electrical stimulation (AE) condition, TINI on the tibial nerve was additionally applied from the AA condition. In the ankle non-assistance (AN) condition, participants wore the device, but assistance was not provided. The joint angles during walking were measured and digitized through a motion analysis system. RESULTS: During a gait cycle, immediate changes in ankle joint motions were observed in the sagittal plane. In the pre-swing phase, ankle dorsiflexion angle was significantly greater in AE condition than AA and AN. There was no significant difference in joint angle between AA and AN. SIGNIFICANCE: This study demonstrates the effectiveness of combining TINI with a wearable robotic ankle device in increasing dorsiflexion angle during the pre-swing phase. This finding provides the feasibility of using TINI as a neuromodulation technique for assisting functional movement in human walking.

Evaluation of the resection efficiency and safety of an enhanced power plasma generator using cadaveric intervertebral discs.

Plasma energy has been used to provide minimally invasive interventional treatment for spinal problems. However, this procedure has been used for limited indications mainly because of its small resection range. To overcome this problem, we designed the enhanced power plasma device. This device seeks to maximize the resection area by modifying the electrode arrangement and enhancing the maximum electric power. The purpose of this study is to assess the efficiency and safety of this newly designed plasma generator, a device for percutaneous disc decompression. We performed an intradiscal procedure on 7 fresh human cadaver lumbar spine specimens using the enhanced power plasma under C-arm fluoroscopic guidance at various voltages. As a result, the volume of the removed area was proportional to the applied magnitude of the electric power level. In particular, under the high-power level condition after 500 s treatment, nearly the entire nucleus pulposus was eliminated. The generated plasma density also tends to grow along with the given electric power. The highest level of temperature rise did not exceed the level that would lead to degeneration in the collagen tissue of the intervertebral disc. Histopathologic examination also demonstrated that there was no thermal damage to the surrounding neural tissues. In conclusion, we speculate that the concepts of this newly designed enhanced plasma generator could be applied to remove huge disc materials without thermal or structural damage to the adjacent target tissues in future spine clinics.

Graph Learning-Based Blockchain Phishing Account Detection with a Heterogeneous Transaction Graph.

Recently, cybercrimes that exploit the anonymity of blockchain are increasing. They steal blockchain users' assets, threaten the network's reliability, and destabilize the blockchain network. Therefore, it is necessary to detect blockchain cybercriminal accounts to protect users' assets and sustain the blockchain ecosystem. Many studies have been conducted to detect cybercriminal accounts in the blockchain network. They represented blockchain transaction records as homogeneous transaction graphs that have a multi-edge. They also adopted graph learning algorithms to analyze transaction graphs. However, most graph learning algorithms are not efficient in multi-edge graphs, and homogeneous graphs ignore the heterogeneity of the blockchain network. In this paper, we propose a novel heterogeneous graph structure called an account-transaction graph, ATGraph. ATGraph represents a multi-edge as single edges by considering transactions as nodes. It allows graph learning more efficiently by eliminating multi-edges. Moreover, we compare the performance of ATGraph with homogeneous transaction graphs in various graph learning algorithms. The experimental results demonstrate that the detection performance using ATGraph as input outperforms that using homogeneous graphs as the input by up to 0.2 AUROC.

External walking environment differentially affects muscle synergies in children with cerebral palsy and typical development.

Despite external environmental changes in walking, such as manipulating gait speed, previous studies have shown that the underlying muscle synergy structures (synergy weights or vectors) rarely vary. The purpose of this study is to examine if external environmental changes to the walking task influence muscle synergies in children with cerebral palsy (CP) and/or typical development (TD). To identify muscle synergies, we extracted muscle synergies from eight children with CP and eight age-matched TD in three treadmill walking conditions, e.g., baseline (adjusted to individual comfortable walking speed), variable speed (VS), or restricted foot width (RW). Then, we grouped similar muscle synergies using k-mean clustering and discriminant analyses from all datasets of individual synergy structures. Proportion tests exhibited six clusters of muscle synergies predominantly arising from children with CP and four clusters from children with TD. Also, the proportion of muscle synergies was significantly different in four of the CP-preferred clusters across conditions. Specifically, the proportion of the baseline condition was significantly different from VS and RW conditions in one and two clusters, respectively. The proportion was significantly different between VS and RW conditions in four clusters. Cadence and step lengths differed across conditions but not groups which makes the group differences in proportion even more notable. In contrast, step width, while significantly lower in CP, did not differ across conditions. Our findings demonstrate that muscle synergies in children with CP are more sensitive to changes in the external walking environment than in typically developing children.

Greater Reliance on Cerebral Palsy-Specific Muscle Synergies During Gait Relates to Poorer Temporal-Spatial Performance Measures.

Children with cerebral palsy typically exhibit reduced complexity of muscle coordination patterns during walking; however, the specific patterns that characterize their gait abnormalities are still not well documented. This study aimed to identify the specific repertoire of muscle coordination patterns in children with CP during walking compared to same-aged peers without CP and their relationships to gait performance. To identify muscle coordination patterns, we extracted muscle synergies from 10 children with CP and 10 age-matched typically developing children (TD). K-mean clustering and discriminant analyses of all extracted synergies were used to group similar synergies. Then, weight-averaged z-scores were quantified for each cluster to determine their group-specific level. In this cohort, 10 of the 17 distinct clusters were largely CP-specific while six clusters were seen mainly in TD, and one was non-specific. CP-specific clusters generally showed merging of two TD synergies, excessive antagonist co-activation, decreased muscle activation compared to TD, and complex or atypical pattern. Significant correlations were found between weight-averaged z-scores and step length asymmetry, cadence asymmetry, self-selected treadmill speed and AP-COM displacement of the pelvis such that greater CP-specificity of muscle synergies was related to poorer performance, thus indicating that CP-specific synergies can influence motor dysfunction.

Mu Rhythm during Standing and Walking Is Altered in Children with Unilateral Cerebral Palsy Compared to Children with Typical Development.

Background: Rehabilitation in cerebral palsy (CP) seeks to harness neuroplasticity to improve movement, including walking, yet cortical activation underlying gait is not well understood. Methods: We used electroencephalography (EEG) to compare motor related cortical activity, measured by mu rhythm, during quiet standing and treadmill walking in 10 children with unilateral CP and 10 age- and sex-matched children with typical development (TD). Peak mu band frequency, mu rhythm desynchronization (MRD), and gait related intra- and inter-hemispheric coherence were examined. Results: MRD during walking was observed bilaterally over motor cortex in both cohorts but peak mu band frequency showing MRD was significantly lower in CP compared to TD. Coherence during quiet standing between motor and frontal regions was significantly higher in the non-dominant compared to dominant hemisphere in CP with no hemispheric differences in TD. Conclusions: EEG-based measures should be further investigated as clinical biomarkers for atypical motor development and to assess rehabilitation effectiveness.

Light Engineering in Nanometer Space.

Significant advances have been made in photonic integrated circuit technology, similar to the development of electronic integrated circuits. However, the miniaturization of cavity resonators, which are the essential components of photonic circuits, still requires considerable improvement. Over the past decades, various optical cavities have been utilized to implement next-generation light sources in photonic circuits with low energy, high data traffic, and integrable physical sizes. Nevertheless, it has been difficult to reduce the size of most commercialized cavities beyond the diffraction limit while maintaining high performance. Herein, recent advancements in subwavelength metallic cavities that can improve performance, even with the use of lossy plasmonic modes, are reviewed. The discussion is divided in three parts according to light engineering methods: subwavelength metal-clad cavities engineered using intermediate dielectric cladding; implementation of plasmonic cavities and waveguides using plasmonic crystals; and development of deep-subwavelength plasmonic waveguides and cavities using geometric engineering. A direction for further developments in photonic integrated circuit technology is also discussed, along with its practical application.

Development and Clinical Evaluation of a Web-Based Upper Limb Home Rehabilitation System Using a Smartwatch and Machine Learning Model for Chronic Stroke Survivors: Prospective Comparative Study.

BACKGROUND: Recent advancements in wearable sensor technology have shown the feasibility of remote physical therapy at home. In particular, the current COVID-19 pandemic has revealed the need and opportunity of internet-based wearable technology in future health care systems. Previous research has shown the feasibility of human activity recognition technologies for monitoring rehabilitation activities in home environments; however, few comprehensive studies ranging from development to clinical evaluation exist. OBJECTIVE: This study aimed to (1) develop a home-based rehabilitation (HBR) system that can recognize and record the type and frequency of rehabilitation exercises conducted by the user using a smartwatch and smartphone app equipped with a machine learning (ML) algorithm and (2) evaluate the efficacy of the home-based rehabilitation system through a prospective comparative study with chronic stroke survivors. METHODS: The HBR system involves an off-the-shelf smartwatch, a smartphone, and custom-developed apps. A convolutional neural network was used to train the ML algorithm for detecting home exercises. To determine the most accurate way for detecting the type of home exercise, we compared accuracy results with the data sets of personal or total data and accelerometer, gyroscope, or accelerometer combined with gyroscope data. From March 2018 to February 2019, we conducted a clinical study with two groups of stroke survivors. In total, 17 and 6 participants were enrolled for statistical analysis in the HBR group and control group, respectively. To measure clinical outcomes, we performed the Wolf Motor Function Test (WMFT), Fugl-Meyer Assessment of Upper Extremity, grip power test, Beck Depression Inventory, and range of motion (ROM) assessment of the shoulder joint at 0, 6, and 12 months, and at a follow-up assessment 6 weeks after retrieving the HBR system. RESULTS: The ML model created with personal data involving accelerometer combined with gyroscope data (5590/5601, 99.80%) was the most accurate compared with accelerometer (5496/5601, 98.13%) or gyroscope data (5381/5601, 96.07%). In the comparative study, the drop-out rates in the control and HBR groups were 40% (4/10) and 22% (5/22) at 12 weeks and 100% (10/10) and 45% (10/22) at 18 weeks, respectively. The HBR group (n=17) showed a significant improvement in the mean WMFT score (P=.02) and ROM of flexion (P=.004) and internal rotation (P=.001). The control group (n=6) showed a significant change only in shoulder internal rotation (P=.03). CONCLUSIONS: This study found that a home care system using a commercial smartwatch and ML model can facilitate participation in home training and improve the functional score of the WMFT and shoulder ROM of flexion and internal rotation in the treatment of patients with chronic stroke. This strategy can possibly be a cost-effective tool for the home care treatment of stroke survivors in the future. TRIAL REGISTRATION: Clinical Research Information Service KCT0004818; https://tinyurl.com/y92w978t.

Children With Unilateral Cerebral Palsy Utilize More Cortical Resources for Similar Motor Output During Treadmill Gait.

Children with unilateral cerebral palsy (CP) walk independently although with an asymmetrical, more poorly coordinated pattern compared to their peers. While gait biomechanics in unilateral CP and their alteration from those without CP have been well documented, cortical mechanisms underlying gait remain inadequately understood. To the best of our knowledge, this is the first study utilizing electroencephalography (EEG) during treadmill gait in older children with and without CP. Lower limb surface electromyographic (EMG) data were collected and muscle synergy analyses performed to quantify motor output. Our primary goal was to evaluate the relationships between cortical and muscle activation within and across groups and hemispheres to provide novel insights into neural control of gait and how it may be disrupted by an early unilateral brain injury. Participants included 9 children with unilateral CP, mean age 16.0 ± 2.7 years, and 12 with typical development (TD), mean age 14.8 ± 3.0 years. EEG data were collected during a standing baseline and treadmill walking at self-selected speed. EMG of 16 lower limb muscles were also collected bilaterally and synchronized with EEG. No significant group differences were found in synergy number or structure across groups. Six cortical clusters were identified as having gait-related activation and all contained participants from both CP and TD groups; however, the percent of individuals per group appearing in different clusters varied. Notably, the cluster least represented in CP was the non-dominant motor region. Both groups showed mu-band ERD in the motor clusters during gait although sustained beta-band ERD was not evident in TD. The CP group showed greater cortical activation than TD during walking as measured by mu- and beta-ERD in the dominant and non-dominant motor and parietal regions and elevated low gamma-activity in the frontal and parietal areas, a unique finding in CP. CP showed greater bilateral motor EEG-EMG coherence in the gamma-band with the hallucis longus compared to TD. In summary, individuals with CP display increased cortical activation during gait possibly relating to differences in distal motor control of the more affected side. Strategies that iteratively reduce cortical activation while improving selective motor control are needed in CP.

Inter-dependence between mathematically independent variability components in human multi-finger force control.

In human movement control, inherent error or uncertainty in the controller, motor system, and sensory system causes variability in motor outcomes. Previous studies have suggested different methods to quantify and examine independent components of the motor variability of motor outputs in a redundant motor system. While these motor variability components are mathematically independent, it is unknown if these components are behaviorally independent among subjects. The aim of this study was to investigate inter-relations between mathematically independent motor variability components in multi-finger force control among subjects. Nineteen healthy subjects performed two tasks, producing a constant force and a sinusoidal force for 12 s over 12 trials. We used the hierarchical variability decomposition (HVD) model to quantify mathematically independent variability components, i.e., online task-relevant variance (onTRV), online task-irrelevant variance (onTIV), offline task-relevant variance (offTRV), and offline task-irrelevant variance (offTIV) for each subject. The correlation analysis performed among all subjects showed that online and offline motor variability components were positively correlated, while task-relevant and -irrelevant variability components were not. The results indicate that these mathematically independent motor variability components existing in multi-finger force space are dependently scaled among subjects, more noticeably between online and offline controls, suggesting a non-independent behavioral relationship between these mathematically independent components among subjects.

Boundary integral equation method for resonances in gradient index cavities designed by conformal transformation optics.

In the case of two-dimensional gradient index cavities designed by the conformal transformation optics, we propose a boundary integral equation method for the calculation of resonant mode functions by employing a fictitious space which is reciprocally equivalent to the physical space. Using the Green's function of the interior region of the uniform index cavity in the fictitious space, resonant mode functions and their far-field distributions in the physical space can be obtained. As a verification, resonant modes in limaçon-shaped transformation cavities were calculated and mode patterns and far-field intensity distributions were compared with those of the same modes obtained from the finite element method.

Transcutaneous high-frequency alternating current for rapid reversible muscle force reduction below pain threshold.

OBJECTIVE: The development of non-invasive, quickly reversible techniques for controlling undesired muscle force production (e.g. spasticity) could expand rehabilitation approaches in those with pathology by increasing the type and intensity of exercises that can be performed. High-frequency alternating current (HFAC) has been previously established as a viable method for blocking neural conduction in peripheral nerves. However, clinical application of HFAC for nerve conduction block is limited due to the invasiveness of surgical procedures and the painful onset response. This study aimed to examine the use of transcutaneous HFAC (tHFAC) at various stimulation frequencies to address these shortfalls. APPROACH: Ten individuals participated in the study. Surface electrodes were utilized to apply tHFAC (0.5-12 kHz) to the median and ulnar nerves. Individual pain threshold was determined by gradual increase of stimulation amplitude. Subjects then performed a force-matching task by producing grip forces up to the maximal voluntary contraction level with and without application of tHFAC below the pain threshold. MAIN RESULTS: Pain threshold current amplitude increased linearly with stimulation frequency. Statistical analysis showed that both stimulation frequency and charge injected per phase had significant effects (p  < 0.05) on grip force reduction. At the group level, application of tHFAC below pain threshold reduced grip force by a maximum of 40.7% ± 8.1%. Baseline grip force trials interspersed between tHFAC trials showed consistent grip force, indicating that fatigue was not a factor in force reduction. SIGNIFICANCE: Our results demonstrate the effectiveness of tHFAC at reducing muscle force when applied below the pain threshold, suggesting its potential clinical viability. Future studies are necessary to further elucidate the mechanism of force reduction before clinical application.

Designing arbitrary-shaped whispering-gallery cavities based on transformation optics.

A novel approach to designing anisotropic whispering gallery modes in gradient index cavities has been reported recently. These cavities, called transformation cavities, can support high-Q whispering gallery modes with directional emission. However, it is usually difficult to find the desired conformal mapping, and it may contain unwanted singularities inside. We show that arbitrary-shaped transformation cavities can be designed by virtue of a quasi-conformal mapping method without confronting such problems. Even though the quasi-conformal mapping method is exploited, we verify that the resulting mappings in our case are strictly conformal. As a demonstration, Q-factor, near field intensity, far field pattern, and phase space description of resonant modes formed in so-designed quadrupole-shaped transformation cavities are presented.

A soft massage tool is advantageous for compressing deep soft tissue with low muscle tension: Therapeutic evidence for self-myofascial release.

OBJECTIVES: This study aimed to compare the amount of deep tissue pressure and muscle relaxation between a soft inflatable rubber ball (SIRB) and a hard massage ball (HMB). DESIGN: Crossover experimental design study. INTERVENTIONS: Thirty participants with neck pain (age: 65.9 ± 3.4, Neck Disability Index score: 34.0% ± 15.2) pillowed a SIRB or an HMB beneath the suboccipital region in the supine position. For the baseline condition, participants pillowed a foam block without a ball. MAIN OUTCOME MEASURES: To quantify the amount of deep-tissue pressure by a ball, compressed soft tissue thickness was measured with lateral cervical radiographs. To assess muscle relaxation, the amount of muscle tension was determined using electromyography of the sternocleidomastoid and upper trapezius muscles. To monitor the cervical lordosis in each condition, the extension angles of the cervical vertebrae were quantified using the relative rotation angles. RESULTS: The compressed soft tissue thickness in the SIRB condition was significantly lower than that in the HMB condition. The normalised muscle activities exhibited that right sternocleidomastoid muscle activity in the HMB condition was significantly higher than that in the baseline and SIRB conditions. In the SIRB and HMB conditions, Numeric Rating Scale for pain was 0.2 ± 0.5 and 5.2 ± 1.4, respectively. CONCLUSIONS: Our findings demonstrate that a SIRB is more advantageous than an HMB for pressing the soft tissue deeply. This finding would be related to reduced muscle tension and discomfort in the SIRB condition when compared with the HMB condition.

Artificial Neural Network Learns Clinical Assessment of Spasticity in Modified Ashworth Scale.

OBJECTIVE: To propose an artificial intelligence (AI)-based decision-making rule in modified Ashworth scale (MAS) that draws maximum agreement from multiple human raters and to analyze how various biomechanical parameters affect scores in MAS. DESIGN: Prospective observational study. SETTING: Two university hospitals. PARTICIPANTS: Hemiplegic adults with elbow flexor spasticity due to acquired brain injury (N=34). INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: Twenty-eight rehabilitation doctors and occupational therapists examined MAS of elbow flexors in 34 subjects with hemiplegia due to acquired brain injury while the MAS score and biomechanical data (ie, joint motion and resistance) were collected. Nine biomechanical parameters that quantify spastic response described by the joint motion and resistance were calculated. An AI algorithm (or artificial neural network) was trained to predict the MAS score from the parameters. Afterwards, the contribution of each parameter for determining MAS scores was analyzed. RESULTS: The trained AI agreed with the human raters for the majority (82.2%, Cohen's kappa=0.743) of data. The MAS scores chosen by the AI and human raters showed a strong correlation (correlation coefficient=0.825). Each biomechanical parameter contributed differently to the different MAS scores. Overall, angle of catch, maximum stretching speed, and maximum resistance were the most relevant parameters that affected the AI decision. CONCLUSIONS: AI can successfully learn clinical assessment of spasticity with good agreement with multiple human raters. In addition, we could analyze which factors of spastic response are considered important by the human raters in assessing spasticity by observing how AI learns the expert decision. It should be noted that few data were collected for MAS3; the results and analysis related to MAS3 therefore have limited supporting evidence.

Muscle Synergies for Turning During Human Walking.

Muscle synergy describes reduced set of functional muscle co-activation patterns. We aimed to identify muscle synergies of turning compared with straight walking. Twelve healthy adults (men: 7, women: 5) performed straight walking (SW), left turning (LT), and right turning (RT) at self-selected speeds. By using non-negative matrix factorization (NMF), we extracted muscle synergies from sixteen electromyography (EMG) signals on the right side and assigned similar muscle synergies among SW, LT, and RT into the same cluster by combining k-means clustering and intraclass correlation coefficient (ICC) analysis. We obtained task-specific clusters of muscle synergies extracted from SW, LT, or RT condition and identified the clusters that share synergies among the conditions. The central nervous system produces specific synergies involving turning behaviors and fundamental synergies for walking.