The COVID-19 pandemic has significantly affected the psychological stability of general population of Pakistan. However, research on the severity of COVID-19 induced depression, anxiety, and stress (DAS) in Pakistan is scarce. This paper thereby investigates the severity of COVID-19 induced DAS based on demographic, socioeconomic, and personal feeling variables by modeling DAS. Snowball sampling strategy was adopted to conduct online survey from July 03, 2021 to July 09, 2021. Out of 2,442, 2,069 responses from Karachi were included. Descriptive and inferential statistics (binary and multinomial logistic regression analysis) were performed using SPSS V21 (IBM, 2013) to identify significant determinants and their association with DAS severity. The result of this study indicates 27.8, 21.7, and 18.3% respondents suffer from severe and extremely severe states of depression, anxiety, and stress, respectively. Binary logistic regression revealed that age is a significant determinant with odds of having 4.72 (95% CI = 1.86–11.97) and 5.86 (95% CI = 2.26–15.2) times greater depression, and stress for respondents aged 19–26 years. Moreover, gender-based difference is also observed with females 1.34 (95% CI = 1.08–1.68) and 1.75 (95% CI = 1.40–2.20) times more likely to exhibit anxiety and stress than males. Furthermore, marital status is a significant determinant of depression with odds of having depression is 0.67 (95% CI = 0.48–0.93) times greater for married population. Multinomial logistic regression revealed that those who believe COVID-19 pandemic has affected them mentally, fear new COVID-19 cases and deaths, depressed due to imposition of lockdown, believe they will not survive COVID-19 infection, and spend more time on social media gathering COVID-19 updates suffer from extremely severe state of depression (OR mental-effect-of-pandemic = 3.70, OR new-COVID-19-cases-and-deaths = 2.20, OR imposition-of-lockdown = 17.77, OR survival-probability = 8.17, OR time-on-social-media = 9.01), anxiety (OR mental-effect-of-pandemic = 4.78, OR new-COVID-19-cases-and-deaths = 3.52, OR imposition-of-lockdown = 5.06, OR survival-probability = 8.86, OR time-on-social-media = 5.12) and stress (OR mental-effect-of-pandemic = 6.07, OR imposition-of-lockdown = 11.38, OR survival-probability = 15.66, OR time-on-social-media = 4.39). Information regarding DAS severity will serve as a platform for research centers and psychological clinics, to work collectively and provide technology-based treatment to reduce the burden on the limited number of psychologist and psychotherapist.

Background. Neuropathic pain (NP) following spinal cord injury (SCI) affects the quality of life of almost 40% of the injured population. The modified brain connectivity was reported under different NP conditions. Therefore, brain connectivity was studied in the SCI population with and without NP with the aim to identify networks that are altered due to injury, pain, or both. Methods. The study cohort is classified into 3 groups, SCI patients with NP, SCI patients without NP, and able-bodied. EEG of each participant was recorded during motor imagery (MI) of paralyzed and painful, and nonparalyzed and nonpainful limbs. Phased locked value was calculated using Hilbert transform to study altered functional connectivity between different regions. Results. The posterior region connectivity with frontal, fronto-central, and temporal regions is strongly decreased mainly during MI of dominant upper limb (nonparalyzed and nonpainful limbs) in SCI no pain group. This modified connectivity is prominent in the alpha and high-frequency bands (beta and gamma). Moreover, oscillatory modified global connectivity is observed in the pain group during MI of painful and paralyzed limb which is more evident between fronto-posterior, frontocentral-posterior, and within posterior and within frontal regions in the theta and SMR frequency bands. Cluster coefficient and local efficiency values are reduced in patients with no reported pain group while increased in the PWP group. Conclusion. The altered theta band connectivity found in the fronto-parietal network along with a global increase in local efficiency is a consequence of pain only, while altered connectivity in the beta and gamma bands along with a decrease in cluster coefficient values observed in the sensory-motor network is dominantly a consequence of injury only. The outcomes of this study may be used as a potential diagnostic biomarker for the NP. Further, the expected insight holds great clinical relevance in the design of neurofeedback-based neurorehabilitation and connectivity-based brain–computer interfaces for SCI patients.

The usage of BLDC motors in the low-power range is increasing rapidly in home appliances such as ceiling fans. This has necessitated the development of reliable, compact and efficient AC-DC power supplies for motor drive circuitry. This paper presents a power supply design consisting of an AC-DC isolated PFC Cuk converter with integrated magnetics that supplies a single-shunt voltage source inverter for the sensorless drive of the BLDC fan motor. The proposed power supply design is comprised of an integrated magnetics structure in which the two inductors and the transformer windings share the same core. The zero input and output ripple current conditions have been derived from the reluctance model of the magnetic assembly. Smooth operation of the motor by minimizing the motor torque ripples is evident from the results. The Cuk converter operates in continuous conduction mode (CCM), employing the current multiplier method. The CCM-based current multiplier control loop ensures a near-unity power factor as well as low total harmonic distortion in the supply current. The current loop also provides over-current protection, enhancing reliability of the system. Moreover, the speed of the BLDC motor is controlled by the field oriented control (FOC) algorithm, which enables direct operation with alternate energy sources such as batteries and solar photovoltaic panels. The performance of the proposed supply is validated: motor torque ripple is reduced to only 2.14% while maintaining 0.999 power factor and only 4.72% THD at full load. Failure modes analysis has also been performed through software simulations, using the PLECS simulation environment. Due to the reliable power supply design with low ripples, it is well suited for low-power BLDC motors in home appliances and small power tools, in addition to ceiling fans.

Brain-computer interface (BCI) is believed to be the translator of brain signals into actions based on the model, built on the machine learning (ML) algorithms, incorporated in it. This study reports on the performance of various ML algorithms in evaluating efficacy of neurofeedback applied for treatment of central neuropathic pain (CNP). In the first phase of this study, we applied different ML algorithms for classification of electroencephalography (EEG) patterns, associated with CNP, obtained from three groups of participants, during imagined movement of their limbs, named as able-bodied (AB), paraplegic patients with (PWP) and without (PNP) neuropathic pain. In the second phase, we tested the accuracy of BCI-classifier by applying new EEG data obtained from PWP participants who have completed neurofeedback training provided for the management of pain. Support vector Machine (SVM) algorithm gained higher accuracy, with all groups, than the other classifiers. However, the highest classification accuracy of 99 ± 0.49% was obtained with the right hand motor imagery of (AB vs PWP) group and 61 electrodes. In Conclusion, SVM based BCI-classifier achieved high accuracy in evaluating efficacy of neurofeedback applied for treatment of CNP. Results of this study show that the accuracy of BCI changes with ML algorithm, electrodes combinations, and training data set.

Trunk stability is important for adequate arm function due to their kinematic linkage. People with Duchenne muscular dystrophy (DMD) can benefit from trunk-assistive devices for seated daily activities, but existing devices limit trunk movement to forward bending. We developed a new trunk orthosis that has spring and pulley design. This study evaluated orthosis performance with 40 able-bodied subjects under with and without orthosis condition in 20 seated tasks for trunk rotation, forward bending, and side bending movements. Subjects adopted static posture in specific trunk orientation while their muscle activity was recorded. They also rated the subjective scales of perceived exertion and usability. A percent change in muscle activity for each task, due to orthosis use, is reported. Significant muscle activity reductions up to 31% and 65% were observed in lumbar and thoracic erector spinae muscles, respectively. Using three-way ANOVA, we found these reductions to be specific to the task direction and the choice of upper limb that is used to perform the asymmetric tasks. A total of 70% participants reported acceptable usability and ~1-point increase in exertion was found for maximum voluntary reaching with the orthosis. The outcomes of this study are promising, though tested on able-bodied subjects. Hence, orthosis mounted on wheelchairs should be further evaluated on DMD patients.