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Chronic obstructive pulmonary disease (COPD) is increasingly being recognized as a systemic disease rather than a mere disorder of the lungs. Central (respiratory) and peripheral (limb) muscle weakness are among the main pronounced systemic effects of COPD. While the disease primarily affects the lower limb muscles and contributes to gait impairment, COPD is also associated with an increasing risk of falls in patients (COPDp). Previous studies have reported higher rates of falls among COPDp (1.17 to 1.20 falls/person-year), amounting to four times higher than an age-matched healthy group. Potential fall risk factors include muscle weakness, impaired daily activities, cognitive dysfunction, and gait and balance impairment. Although COPDp often manifest many of these risk factors, there remains a gap in literature regarding falls during walking in this population. This study aimed to 1. analyze the literature to identify the risk factors of falling in COPDp, and 2. investigate the underlying mechanisms by which these risk factors can lead to increased prevalence of falling. The results suggest that in addition to the known risk factors of falling, low back pain and mental fatigue should also be considered as relevant risk factors in the treatment process of these patients. Moreover, respiratory problems, which are common in this population, have demonstrated pronounced effects on energy expenditure, gait, and other types of activities of daily living (ADLs), leading to reduced intensity, disrupted coordination of the trunk-pelvic structure with the lower limbs during gait, and altered motor control performance due to activation of muscles in an inefficient synergic manner. These problems potentially lead to the increased vulnerability of these patients to external disturbances and higher incidence risk of falls and injuries. Cognitive problems, which are typically due to reduced oxygen received by the brain, as well as general inflammation caused by COPD, also play a significant role in gait disruption and balance. Future research is warranted to determine the prevalence of falls in COPDp by examining the response of these patients to Medio-Lateral (ML) and Anterior-Posterior (AP) disturbances during gait in association with traditional and recommended fall risk factors.

Background and Aim Considering the importance of non-specific low back pain (NSLBP) and its increasing spread, the need for instruments for the accurate diagnosis of back pain is evident in order to offer more effective treatment. One such instrument is the STarT Back Screening Tool (STarT) which is examined by numerous studies, while some of its psychometric dimensions still require attention. Therefore, the objective of this study was to assess the internal consistency and construct validity of this questionnaire to propose a modified version. Method In this cross-sectional study, the data of 295 patients with NSLBP were analyzed. Cronbach's alpha was used to assess internal consistency, and exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to assess construct validity. The Χ2/df, GFI, CFI, and RMSEA indices were also utilized as the goodness-of-fit criteria. Data analysis was performed in SPSS, AMOS, and EQS programs. Results Goodness-of-fit indicators were calculated for the original Persian version of the questionnaire, showing an improper fit (RMSEA = 0.162). According to the measures of sampling adequacy (MSA) of the questions, Questions 1 and 8 were deleted, resulting in an improved index (RMSEA = 0.062). All the regression coefficients in the CFA model were significant (p Conclusion Based on the results, the modified Persian version of the STarT is simpler and more practical than the previous version, serving as a valid and reliable tool for assessing patients with low back pain. With respect to the goodness-of-fit indices, we recommend that more studies with larger samples be conducted on different populations.

Background: The Tampa Scale of Kinesiophobia (TSK) is considered a valid and reliable tool to assess the fear-avoidance behavior in patients. There is a valid and reliable Persian version of the TSK-17. Objectives: The present study aimed to assess the internal consistency as a measurement for the test reliability and factor (domain) validity of the Persian version of the TSK-17 to determine whether a modified form can be proposed. Methods: This study analyzed the data of 295 individuals with non-specific low back pain (NSLBP). Cronbach’s alpha was used to assess internal consistency (reliability). Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were applied to evaluate factor validity which is an aspect of the construct validity. The Chi-square divided by the degrees of freedom, the goodness of fit index (GFI), the confirmatory fit index (CFI), and the root mean square error of approximation (RMSEA) indices were utilized as the goodness-of-fit criteria. Data analysis was performed using SPSS software (version 18), AMOS software (version 20), and EQS software (version 6.2). Results: Two factors were extracted for the TSK-17 questionnaire using EFA, and then the structure was confirmed with CFA. Cronbach’s alpha as an internal consistency index was 0.949 for the entire questionnaire, 0.931 for the 11-item fear-of-movement factor, and 0.971 for the 6-item belief factor. The evaluation of the inappropriate items demonstrated that no items were selected for the deletion; therefore, a modified version of the TSK was not presented. The goodness-of-fit indices were reported as GFI = 0.882, RMSEA=0.066 (90% CI: 0.055-0.076), CFI = 0.983, and minimum discrepancy per degree of freedom = 2.27. Conclusions: The Persian version of the TSK-17 can be considered a valid and reliable tool to assess the fear of movement and avoidance behavior in individuals with NSLBP.

Background: Chronic Obstructive Pulmonary Disease (COPD) leads to limited activity and reduced quality of life. Treatment of this disease is a long-term process that requires the cooperation of patients in monitoring and treatment. Methods: In the present study which was conducted from April 2019 to March 2021 in Masih Daneshvari Hospital, Tehran, Iran, 75 patients were randomly divided into telerehabilitation and control groups. Patients in the control group received pulmonary rehabilitation including respiratory, isometric, and aerobic exercises for 8 weeks, three times per week. In the second group, patients were given a lung rehabilitation booklet and asked to repeat the exercises three times a week for four weeks according to a specific schedule. In addition, patients installed Behzee care application on the mobile phone that recorded various indicators such as heart rate, SpO2, dyspnea, fatigue, and daily activities. This application reminded the patient of the program every day and at a specific time. Finally, the patients’ conditions were compared in the two groups after 8 weeks using CAT and mMRC questionnaires and 6-Minute Walk (6MW) exercise indices as well as spirometry tests. Results: In all four indicators (6MW, CAT, and mMRC questionnaires as well as spirometry), patients showed improvement after rehabilitation (p

Background: The risk of falling in patients with chronic obstructive pulmonary disease (COPD) is higher than healthy people, imposing a great financial burden on patients due to clinical diagnosis and treatment. This study aimed to compare static balance between two groups of healthy people and COPD patients, based on cognitive tasks and vision tests, using linear and non-linear analyses. Materials and Methods: A total of 15 patients with COPD and 14 age- and gender-matched healthy individuals were recruited in this study. Variations in the center of pressure were recorded in both medial-lateral (ML) and anterior-posterior (AP) directions by implementing visual feedback and cognitive tasks, with the subject standing on a force plate. Data related to the center of pressure were analyzed in the AP and ML directions by linear methods (i.e., standard deviation of displacement, standard deviation of maximum velocity, average velocity, and phase plane). Also, the nonlinear method (Lyapunov exponents) was used in both directions. Results: The cognitive tasks improved the center of pressure variables in both groups. In association with the vision tests, only lack of vision had a significant effect on the patients. The results of the linear analysis in the ML direction were significantly higher in the COPD group as compared to the healthy group; however, the results were not significant in the AP direction. Also, the non-linear analysis showed significant differences between the groups. Conclusion: Use of both linear and non-linear analyses is necessary for evaluating the balance of patients with breathing difficulties. Balance disorders in COPD patients were mostly in the ML direction; therefore, postural deformities might be one of the reasons for balance problems in the AP direction.

We propose a cell planning method for wireless cellular networks to simultaneously balance the volume shares of the cells and to preserve their regularity. In this framework, we first optimize the base station locations to minimize the coefficient of variation (CoV)-based service demand share metric using the power Voronoi algorithm. Then, we maximize the downlink coverage probability by defining a local regularity optimization problem and solve it through particle swarm, farthest point, average point, and spatial median optimization methods. Finally, we apply the proposed methods on a real network to show how the proposed methods simultaneously minimize both CoV-based service demand share and local regularity metrics.

Central nervous system (CNS) uses vision, vestibular, and somatosensory information to maintain body stability. Research has shown that there is more lumbar proprioception error among low back pain (LBP) individuals as compared to healthy people. In this study, two groups of 20 healthy people and 20 non-specific low back pain participants (LBP) took part in this investigation. This investigation focused on somatosensory sensors and in order to alter proprioception, a vibrator (frequency of 70Hz, amplitude of 0.5 mm) was placed on the soleus muscle area of each leg and two vibrators were placed bilaterally across the lower back muscles. Individuals, whose vision was occluded, were placed on two surfaces (foam and rigid) on force plate, and trunk angles were recorded simultaneously. Tests were performed in 8 separate trials; the independent variables were vibration (4 levels) and surface (2 levels) for within subjects and 2 groups (healthy and LBP) for between subjects (4×2×2). MANOVA and multi-factor ANOVA tests were done. Linear parameters for center of pressure (COP) (deviation of amplitude, deviation of velocity, phase plane portrait (PPP), and overall mean velocity) and nonlinear parameters for COP and trunk angle ((recurrence quantification analysis) RQA and Lyapunov exponents) were chosen as dependent variables. Results indicated that NSLBP individuals relied more on ankle proprioception for postural stability. Similarly, RQA parameters for the COP on both sides and for the trunk sagittal angle indicated more repeated patterns of movement among the LBP cohort. Analysis of short and long Lyapunov exponents showed that people with LBP caused no use of all joints in their bodies (non-flexible), are less stable than healthy subjects.

Background: Various studies have reported that the pelvic girdle and lumbar spine are reflexively stabilized and braced prior to the initiation of extremity movements. Objectives: The present study aimed to assess the reliability of the diaphragm muscle thickness and excursion measured by rehabilitative ultrasound imaging (RUSI). Methods: This is a cross-sectional study that was done in the physiotherapy department of the Faculty of Rehabilitation at the Shahid Beheshti University of Medical Sciences (Tehran, Iran) in 2019. Images of diaphragm thickness were taken using RUSI in the intercostal space between the 7th and 8th, or 8th and 9th ribs, at which the diaphragm was more easily visualized. The diaphragm motion assessment was performed by applying the transducer on the abdomen at the right midclavicular line. Imaging was conducted in 10 participants with pelvic girdle pain (PGP) and 10 asymptomatic women and men aged 20 - 44 years. Images were obtained by one examiner, muscle thickness was measured using B mode RUSI, and the motion was assessed using M mode RUSI. All assessments were performed in quiet breathing and deep breathing states. Intraclass correlation coefficients (ICC), standard error of measurement (SEM), and minimal detectable change (MDC) were used for reliability assessment. Results: The ICC, SEM, and MDC values revealed an excellent intrarater reliability for RUSI in both groups to measure the diaphragm thickness (ICC between 0.88 to 0.92). Measurement of diaphragm excursion demonstrated excellent reliability in the asymptomatic group (ICC between 0.80 to 0.90) and less reliability, between good and excellent, in the PGP group (ICC between 0.74 to 0.79). Conclusions: The method of RUSI employed in the present study is recommended for measuring diaphragm thickness and motion in patients with PGP.

Low back pain (LBP) remains a critical health issue impacting literally millions of people worldwide. Currently, clinical practitioners rely on subjective measures such as the STarT Back Screening Tool to categorize LBP patients, which then informs specific treatment regimens. This study sought to develop a machine learning model to classify LBP patients into different groups according to kinematic data. Specifically, an inertial measurement unit (IMU) was attached to each patient’s chest while he performed trunk flexion/extension motions at a self-selected pace. Machine learning algorithms such as support vector machine (SVM) and multi-layer perceptron (MLP) were implemented to evaluate the efficiency of the models. The results showed that the kinematic data we obtained could be used to categorize the patients into two groups: high vs. low-medium risk. We achieved accuracy levels of ~75% and 60% for SVM and MLP, respectively. Additionally, among a range of variables detailed herein, we determined that time-scaled IMU signal resulted in the highest accuracy. Our findings support the use of body-motion measures in developing prognosis tools for healthcare applications. Our results could help overcome the need for objective clinic-based diagnosis approaches, which in turn would lead to assigning better treatment approaches and rehabilitation services for LBP sufferers.

In this study, an enhanced short-time Fourier transform (STFT)-based jamming mitigation system which employs several windows to increase time–frequency (t–f) plane resolution is proposed. A technique for employing near-optimum windows is also proposed. It is observed that selection of these windows leads to increasing the resolution of the t–f representation. An infinite impulse-response notch filter is employed for jamming removal process. Performance of the proposed method is evaluated by a set of measured global positioning system data. It is compared with conventional STFT-based algorithms reported in literature.

Background: The Nijmegen questionnaire is one of the most common tools for diagnosing hyperventilation syndrome (HVS). However, there is no precise cut-off score for differentiating patients with HVS from those without HVS. This study was conducted to evaluate the accuracy of Nijmegen questionnaire for detecting patients with HVS and to provide the best cut-off score for differentiating patients with HVS from normal individuals using a Bayesian model in the absence of a gold standard. Materials and Methods: A total of 490 students from a rehabilitation center in Tehran, Iran, were asked to participate in this case study of HVS from January to August 2018. Results: A total of 215 students (40% male and 60% female) completed the Nijmegen questionnaire. The area under the receiver operating characteristic curve (AUC) was 0.93 (male: 0.95; female: 94) for all of the cut-off scores. The optimal cut-off score of ≥20 could predict HVS with sensitivity of 0.91 (male: 0.99; female: 91) and specificity of 0.92 (male: 96; female: 89). Conclusion: Accurate differentiation of HVS patients from individuals without HVS can be accomplished by estimating the cut-off score of Nijmegen questionnaire based on a non-parametric Bayesian model. [GMJ.2020;9:e1738]

We study the optimal location of Access Points (AP) in cellular networks with irregular service demand distribution, using a power Voronoi algorithm. To this end, we propose two weights updating approaches to acquire uniform load pattern with uniform power allocation at all APs. In Channel-based Power Voronoi Algorithm (CPVA), we update the Voronoi weights based on the approximated loads imposed to APs assuming that the cell load is only a function of traffic and the channel coefficients between the AP and the associated users. In Load-based Power Voronoi Algorithm(LPVA), the weights are updated by load calculation through a convex optimization problem in cell load coupling model. It is worth noting that in both methods, approximately uniform load patterns are derived with uniform power allocation at APs, which guarantees the quality of service and energy efficiency in the network. We also remark that LPVA outperforms CPVA at the cost of higher computational cost. Finally, the results of both method are compared to prior art to show the advantages of applying CPVA and LPVA in cellular network planning.

Gait recovering after spinal cord injury (SCI) is a regular attempt in neurorehabilitation. For this purpose, various clinical techniques have been proposed until now. However, the feasibility of these techniques has not been theoretically investigated so much. This has been mainly for difficulties of gait modeling in SCI patients. Involving these problems, recently neuromechanical models of gait locomotion have been proposed for examining rehabilitation methods. However, these models were so simple that could not properly express rehabilitation effects. Notably, lesion intensity is a concern that was never attended in prior simulations. Due to this limitation, in this paper a new neuromechanical model is proposed that classifies patients based on intensity of trauma. Explicitly, the complete, severe and non-severe incomplete SCIs are imitated and effects of related clinical rehabilitations are explored. Remarkably, the model indicates an incredible performance in explaining the rehabilitation effects through presenting the compliant results with clinical information. The suitability of this model is mainly for the applied neuromuscular plan that consists of a combined plan of central pattern generator (CPG) and neural reflexes that controls a double segment limb. The validity of this model is further proved by comparing the kinematic and kinetic results to the experimental data.

To translate the STarT Back Screening Tool (SBT) into Persian and to investigate the psychometric properties of the new version in a group of patients with Non-Specific Low Back Pain (NSLBP).The STarT is a validated questionnaire used for subgrouping LBP patients at three levels of low-, medium-, and high-risk, based on the risk of chronicity. It has previously been translated and validated in different languages.The translation and validation of the original questionnaire were carried out in accordance with the standard guidelines. To approve the construct validity, 295 patients with NSLBP completed a questionnaire package. The package comprised of the STarT, Roland-Morris Disability questionnaire (RMDQ), Tampa Scale for Kinesiophobia (TSK), Coping Strategies Questionnaire (CSQ), and Hospital Anxiety and Depression Scale (HADS). To evaluate test-retest reliability, 35 randomly selected NSLBP patients completed the STarT questionnaire within min. 24-hour interval.Factor analysis confirmed two subscales of the STarT. The Cronbach α was .83 and .81 for the STarT and the subscale, respectively. This questionnaire showed excellent test-retest reliability (ICC = .85) (p0.01). The correlations between the STarT and RMDQ, CSQ, TSK, and the two subscales of HADS were estimated to be .81, .70, .71, .74, and .71, respectively. The Area under the Curve was also calculated for 6 items and the range was between .734 and .860.The Persian version of the STarT is reliable and valid, and consistent with the original questionnaire. Therefore, clinicians to subgroup Persian-speaking NSLBP patients can use it.

In this study, a new approach to improve antifouling performance of polyacrylonitrile (PAN) hollow fiber membrane has been explained. Firstly, chemical modification with sodium hydroxide (NaOH) solution was performed on PAN membranes in various conditions, so that, as a result of hydrolysis, carboxyl groups emerge on membrane surface. Then, in order to improve surface hydrophilicity, the hydrolyzed membrane underwent a polyethylene glycol (PEG) deposition through a chemical reaction. Chemical changes in membrane were characterized via Fourier transform infrared spectroscopy/attenuated total reflectance (FTIR/ATR). In addition, measurement of contact angle and fouling test were performed to analyze hydrophilicity degree and performance of modified membrane, respectively. Results of measuring contact angle signified improvement of hydrophilicity of membrane after modification. Modified membranes showed lower tendency to foul during ultrafiltration (UF) of milk solution, which is confirmed by increase in flux recovery ratio (FRR) level following membrane modification. Three hours after hydrolysis process, though pure water flux through membrane reduced by 28% comparing with intact membrane, the level of polyvinyl alcohol (PVA-30 kDa) rejection and FRR increased 13 and 14%, respectively. Upon attachment of PEG to the membrane surface, the contact angle reduced from 64° for non-modified membrane to 21°.

In this study, a new method was applied to achieve an efficient surface modification of Polyacrylonitrile (PAN) hollow fiber membrane. The surface modification dealt by immersion of PAN hollow fibers in hydroxylamine solution under various conditions (different solution concentrations and reaction time). The nitrile groups on the surface of the membrane were changed to form the amidoxime (-C(NH2)=N-OH) groups. The surface modified membranes were assessed by pure water permeation test and the rejection of high molecular weight materials like Polyvinylalcohol (PVA) from water. Permeation test results showed that with increasing hydroxylamine concentration, the amount of water permeation reduces slowly, while the PVA-30 kDa rejection has been somewhat increased after surface modification. FTIR/ATR analysis confirms the presence of amidoxime groups on the membrane surface. Also, the water contact angel was decreased from 64 to 34 after reaction. The ability of silver ions absorption was also assessed for modified membrane. Finally, the antifouling property of the modified hollow fibers was assessed by milk solution ultrafiltration. The obtained results showed that the modified hollow fibers present better antifouling properties.

This paper presents a novel approach for evaluating LBP in various settings. The proposed system uses cost-effective inertial sensors, in conjunction with pattern recognition techniques, for identifying sensitive classifiers towards discriminate identification of LB patients. 24 healthy individuals and 28 low back pain patients performed trunk motion tasks in five different directions for validation. Four combinations of these motions were selected based on literature, and the corresponding kinematic data was collected. Upon filtering (4th order, low pass Butterworth filter) and normalizing the data, Principal Component Analysis was used for feature extraction, while Support Vector Machine classifier was applied for data classification. The results reveal that non-linear Kernel classification can be adequately employed for low back pain identification. Our preliminary results demonstrate that using a single inertial sensor placed on the thorax, in conjunction with a relatively simple test protocol, can identify low back pain with an accuracy of 96%, a sensitivity of %100, and specificity of 92%. While our approach shows promising results, further validation in a larger population is required towards using the methodology as a practical quantitative assessment tool for the detection of low back pain in clinical/rehabilitation settings.

Since the past decade, rehabilitation robots have become common technologies for recovering gait ability after a stroke. Nevertheless, it is believed that these robots can be further enhanced. Hence, several researches are making progress in optimizing gait rehabilitation robots. However, most of these researches have only assessed the robots and their controllers in improving spatiotemporal and kinetic features of walking. There are not many researchers have focused on the robots’ controllers’ effects on the central nervous or neuromuscular systems. On the other hand, recently computational methods have been utilized to investigate the rehabilitations of neural disorders, through developing neuromechanical models. However, these methods have neither studied the robot-assisted gait rehabilitation, nor have they theoretically proved why rehabilitation exercises enhance patients’ walking ability. Therefore, this paper merged a theoretical approach into a computational method to investigate the effects of gait rehabilitation robots on post-stroke neuromuscular system. To this end, a neuromechanical model of gait has been developed and thereby, the Poincare maps of intact and stroke people have been obtained. Comparison of these maps revealed why a stroke reduces the stability of walking. Then, the effect of an impedance controller, which is used in a rehabilitative robot, is scrutinized in stabilizing a walking motion. Obtaining the Poincare map of this close-loop system, proved that this controller improves motion stability. Finally, the effect of this controller is investigated by simulations and experiments. The experimental tests are performed by Arman rehabilitative robot. Clinical Reference Number: IR.TMU.REC.1394.254.

In this paper, we study three cooperative transmission schemes by use of amplify-and-forward (AF) relaying strategies. It is assumed that there is one source, one destination and several AF-relays. First, a parallel-relay strategy is considered wherein the transmitted message from the source is received by each relay independently. Then, the relay retransmit the message by use of AF relaying to the destination. Next, we consider the case where the message is being sent through the whole relays sequentially to the destination. Finally, we consider a general case, where we have multi-branches such that on each branch, there exist several relays sequentially cooperating to transmit the message to the destination. For each cooperative transmission scheme, we are looking for minimizing the symbol-error rate (SER) subject to sum-relay power (SRP). Hence, for each cooperative transmission schemes, we analyze the optimization problem and analytically derive the optimal power allocation at the relays to minimize the SER. Finally, we numerically show that when the SRP is low, we can optimize the number of active relays. That is, at low SRP increasing number of relays does not monotonically decrease the SER. On the other hand, at high SRP, employing more number of relays is more beneficial than allocating more power to a limited number of relays.