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Assessment of Gait Symmetry Improvements in National Athletes after Anterior Cruciate Ligament Reconstruction during Rehabilitation

Hadizadeh M, Amri S, Roohi SA, Mohafez H

Int J Sports Med, 2016 Nov;37(12):997-1002.
PMID: 27551935

This study aimed to quantify changes in gait parameters and their symmetries among athletes with anterior cruciate ligament (ACL) reconstructions during a rehabilitation program. Twenty-two national players with ACL reconstructions and 15 healthy athletes were recruited. The gait data were collected between postoperative weeks 4-5, 8-9 and 12-13 using a three-dimensional motion analysis system. The spatio-temporal gait parameters and symmetry indexes (SIs) were evaluated for the patients and the control group. One-way and repeated-measures multivariate analysis of variance were used to analyse the data. The results demonstrated significant differences among spatio-temporal (P<0.001) and SIs (P=0.007) of patients for Test 1 and the control group. Repeated measure analysis revealed significant changes in the linear combinations of spatio-temporal gait variables (P=0.002) and SIs (P=0.043) over time. The injured limb's step length, cadence and weight acceptance time presented significant improvement across time (P<0.001). Moreover, the SI of the stance time was reduced significantly by 46.48% (P=0.004) among SI parameters. After three months, no significant differences were found between patients and healthy controls for the measured gait components (P>0.05). The rehabilitation program allowed national athletes to restore symmetry in spatio-temporal gait parameters toward the control group's range 12-13 weeks post-reconstruction.
Gait analysis of national athletes after anterior cruciate ligament reconstruction following three stages of rehabilitation program: Symmetrical perspective

Hadizadeh M, Amri S, Mohafez H, Roohi SA, Mokhtar AH

Gait Posture, 2016 07;48:152-158.
PMID: 27318454 DOI: 10.1016/j.gaitpost.2016.05.002

This study aimed to objectively evaluate changes in gait kinematics, kinetics and symmetry among anterior cruciate ligament (ACL) reconstructed athletes during rehabilitation. Twenty-two national athletes with ACL reconstruction and 15 healthy athletes were recruited for the study. Gait data were collected between the weeks 4-5, 8-9, and 12-13 post-operation using three-dimensional motion analysis system. Five separate components, including knee range of motion (ROM), vertical ground reaction force (VGRF), their symmetries and knee extension moment were evaluated. One way and repeated measure multivariate analysis of variance (MANOVA) were used to analyze the knee ROMs. The VGRF and extension moment were tested using repeated measure ANOVA and independent sample t-test. Findings indicated significant alterations in all measured components between patients' Test 1 and control group. Repeated measure analysis revealed significant effect for time in components of knee angular and VGRF (P<0.001), their symmetry index (P=0.03) and knee extension moment (P=0.045). Univariate outcomes demonstrated significant improvement in the injured limb's stance and swing (P<0.001), and single-stance (P=0.005) ROMs over time. Symmetry indexes of stance and swing ROM, and VGRF reduced significantly by 26.3% (P=0.001), 17.9% (P<0.001), and 31.9% (P=0.03) respectively. After three months, symmetry indexes of single-stance ROM and VGRF along with operated knee extension moment were the only variables which showed significant differences with control group. The rehabilitation program allowed national athletes to restore the operated limb's gait parameters except knee extension moment by 12-13 weeks post-reconstruction; however, more time is required to normalize single-stance ROM and VGRF asymmetries.
Quantitative assessment of wound healing using high-frequency ultrasound image analysis

Mohafez H, Ahmad SA, Hadizadeh M, Moghimi S, Roohi SA, Marhaban MH, et al.

Skin Res Technol, 2018 Feb;24(1):45-53.
PMID: 28557064 DOI: 10.1111/srt.12388

PURPOSE: We aimed to develop a method for quantitative assessment of wound healing in ulcerated diabetic feet.
METHODS: High-frequency ultrasound (HFU) images of 30 wounds were acquired in a controlled environment on post-debridement days 7, 14, 21, and 28. Meaningful features portraying changes in structure and intensity of echoes during healing were extracted from the images, their relevance and discriminatory power being verified by analysis of variance. Relative analysis of tissue healing was conducted by developing a features-based healing function, optimised using the pattern-search method. Its performance was investigated through leave-one-out cross-validation technique and reconfirmed using principal component analysis.
RESULTS: The constructed healing function could depict tissue changes during healing with 87.8% accuracy. The first principal component derived from the extracted features demonstrated similar pattern to the constructed healing function, accounting for 86.3% of the data variance.
CONCLUSION: The developed wound analysis technique could be a viable tool in quantitative assessment of diabetic foot ulcers during healing.
Fulltext Effects of Tele-Pilates and Tele-Yoga on Biochemicals, Physical, and Psychological Parameters of Females with Multiple Sclerosis

Najafi P, Hadizadeh M, Cheong JPG, Mohafez H, Abdullah S, Poursadeghfard M

J Clin Med, 2023 Feb 16;12(4).
PMID: 36836119 DOI: 10.3390/jcm12041585

BACKGROUND: People with multiple sclerosis (PwMS) suffer from some comorbidities, including physical and psychiatric disorders, low quality of life (QoL), hormonal dysregulation, and hypothalamic-pituitary-adrenal axis dysfunction. The current study aimed to investigate the effects of eight weeks of tele-yoga and tele-Pilates on the serum levels of prolactin and cortisol and selected physical and psychological factors.
METHODS: Forty-five females with relapsing remitting multiple sclerosis, based on age (18-65), expanded disability status scale (0-5.5), and body mass index (20-32), were randomly assigned to tele-Pilates, tele-yoga, or control groups (n = 15). Serum blood samples and validated questionnaires were collected before and after interventions.
RESULTS: Following online interventions, there was a significant increase in the serum levels of prolactin (p = 0.004) and a significant decrease in cortisol (p = 0.04) in the time × group interaction factors. In addition, significant improvements were observed in depression (p = 0.001), physical activity levels (p < 0.001), QoL (p ≤ 0.001), and the speed of walking (p < 0.001).
CONCLUSION: Our findings suggest that tele-yoga and tele-Pilates training could be introduced as patient-friendly, non-pharmacological, add-on therapeutic methods for increasing prolactin and decreasing cortisol serum levels and achieving clinically relevant improvements in depression, walking speed, physical activity level, and QoL in female MS patients.
Effects of tele-exercise training on physical and mental health and quality of life in multiple sclerosis: Do the effects differ by modality and clinical disease course?

Najafi P, Hadizadeh M, Cheong JPG, Motl RW, Abdullah S, Mohafez H, et al.

Mult Scler Relat Disord, 2023 Dec;80:105129.
PMID: 37977056 DOI: 10.1016/j.msard.2023.105129

INTRODUCTION: Tele-exercise training has improved mental and physical health and quality of life (QOL) in people with multiple sclerosis (PwMS), but there is little known about the comparability of effects across modalities and clinical disease courses.
OBJECTIVE: To evaluate the effect of tele-Pilates and tele-yoga training on physical and mental factors and QOL in PwMS, with a focus on two phenotype classifications - relapsing-remitting MS (RRMS) and secondary progressive MS (SPMS).
METHODS: Eighty-two persons with RRMS (n = 48) and SPMS (n = 34) were randomly assigned into tele-Pilates (n = 29), tele-yoga (n = 26), or control (n = 27). The tele-exercis training was conducted three times per week for eight weeks.
RESULTS: Significant time × group interactions were observed for QoL (p = 0.01), physical activity levels (p < 0.001), mental health (p = 0.05), and a decline in depression (p = 0.002) following tele-Pilates and tele-yoga. The corresponding subfactors, including pain, energy, emotional well-being, and role limitation due to emotional and physical problems, have shown significant improvements after interventions compared with control (all p < 0.05). The effects of exercise over control did not depend on MS phenotype (all p > 0.05).
DISCUSSION: Tele-yoga and tele-Pilates exercises improved QoL and mental and physical health in PwMS, and the benefits were similar across both MS phenotypes. These findings highlight the potential of implementing tele-yoga and tele-Pilates as non-pharmacological mind-body symptomatic treatments for individuals with both RRMS and SPMS.
Fulltext The Promise for Reducing Healthcare Cost with Predictive Model: An Analysis with Quantized Evaluation Metric on Readmission

Teo K, Yong CW, Muhamad F, Mohafez H, Hasikin K, Xia K, et al.

J Healthc Eng, 2021;2021:9208138.
PMID: 34765104 DOI: 10.1155/2021/9208138

Quality of care data has gained transparency captured through various measurements and reporting. Readmission measure is especially related to unfavorable patient outcomes that directly bends the curve of healthcare cost. Under the Hospital Readmission Reduction Program, payments to hospitals were reduced for those with excessive 30-day rehospitalization rates. These penalties have intensified efforts from hospital stakeholders to implement strategies to reduce readmission rates. One of the key strategies is the deployment of predictive analytics stratified by patient population. The recent research in readmission model is focused on making its prediction more accurate. As cost-saving improvements through artificial intelligent-based health solutions are expected, the broad economic impact of such digital tool remains unknown. Meanwhile, reducing readmission rate is associated with increased operating expenses due to targeted interventions. The increase in operating margin can surpass native readmission cost. In this paper, we propose a quantized evaluation metric to provide a methodological mean in assessing whether a predictive model represents cost-effective way of delivering healthcare. Herein, we evaluate the impact machine learning has had on transitional care and readmission with proposed metric. The final model was estimated to produce net healthcare savings at over $1 million given a 50% rate of successfully preventing a readmission.
Fulltext Discovering Knee Osteoarthritis Imaging Features for Diagnosis and Prognosis: Review of Manual Imaging Grading and Machine Learning Approaches

Teoh YX, Lai KW, Usman J, Goh SL, Mohafez H, Hasikin K, et al.

J Healthc Eng, 2022;2022:4138666.
PMID: 35222885 DOI: 10.1155/2022/4138666

Knee osteoarthritis (OA) is a deliberating joint disorder characterized by cartilage loss that can be captured by imaging modalities and translated into imaging features. Observing imaging features is a well-known objective assessment for knee OA disorder. However, the variety of imaging features is rarely discussed. This study reviews knee OA imaging features with respect to different imaging modalities for traditional OA diagnosis and updates recent image-based machine learning approaches for knee OA diagnosis and prognosis. Although most studies recognized X-ray as standard imaging option for knee OA diagnosis, the imaging features are limited to bony changes and less sensitive to short-term OA changes. Researchers have recommended the usage of MRI to study the hidden OA-related radiomic features in soft tissues and bony structures. Furthermore, ultrasound imaging features should be explored to make it more feasible for point-of-care diagnosis. Traditional knee OA diagnosis mainly relies on manual interpretation of medical images based on the Kellgren-Lawrence (KL) grading scheme, but this approach is consistently prone to human resource and time constraints and less effective for OA prevention. Recent studies revealed the capability of machine learning approaches in automating knee OA diagnosis and prognosis, through three major tasks: knee joint localization (detection and segmentation), classification of OA severity, and prediction of disease progression. AI-aided diagnostic models improved the quality of knee OA diagnosis significantly in terms of time taken, reproducibility, and accuracy. Prognostic ability was demonstrated by several prediction models in terms of estimating possible OA onset, OA deterioration, progressive pain, progressive structural change, progressive structural change with pain, and time to total knee replacement (TKR) incidence. Despite research gaps, machine learning techniques still manifest huge potential to work on demanding tasks such as early knee OA detection and estimation of future disease events, as well as fundamental tasks such as discovering the new imaging features and establishment of novel OA status measure. Continuous machine learning model enhancement may favour the discovery of new OA treatment in future.
Fulltext Degradation of Perovskite Thin Films and Solar Cells with Candle Soot C/Ag Electrode Exposed in a Control Ambient

Islam MA, Mohafez H, Sobayel K, Wan Muhamad Hatta SF, Hasan AKM, Khandaker MU, et al.

Nanomaterials (Basel), 2021 Dec 20;11(12).
PMID: 34947812 DOI: 10.3390/nano11123463

Perovskite solar cells (PSCs) have already achieved efficiencies of over 25%; however, their instability and degradation in the operational environment have prevented them from becoming commercially viable. Understanding the degradation mechanism, as well as improving the fabrication technique for achieving high-quality perovskite films, is crucial to overcoming these shortcomings. In this study, we investigated details in the changes of physical properties associated with the degradation and/or decomposition of perovskite films and solar cells using XRD, FESEM, EDX, UV-Vis, Hall-effect, and current-voltage (I-V) measurement techniques. The dissociation, as well as the intensity of perovskite peaks, have been observed as an impact of film degradation by humidity. The decomposition rate of perovskite film has been estimated from the structural and optical changes. The performance degradation of novel planner structure PSCs has been investigated in detail. The PSCs were fabricated in-room ambient using candle soot carbon and screen-printed Ag electrode. It was found that until the perovskite film decomposed by 30%, the film properties and cell efficiency remained stable.
Fulltext Microplastics pollution in salt pans from the Maheshkhali Channel, Bangladesh

Rakib MRJ, Al Nahian S, Alfonso MB, Khandaker MU, Enyoh CE, Hamid FS, et al.

Sci Rep, 2021 11 30;11(1):23187.
PMID: 34848770 DOI: 10.1038/s41598-021-02457-y

Microplastics (MP) were recognized as an emergent pollution problem due to their ubiquitous nature and bioaccumulative potential. Those present in salt for consumption could represent a human exposure route through dietary uptake. The current study, conducted in Bangladesh, reports microplastics contamination in coarse salt prepared for human consumption. Sea salt samples were collected from eight representative salt pans located in the country's largest salt farming area, in the Maheshkhali Channel, along the Bay of Bengal. Microplastics were detected in all samples, with mean concentrations ranging from 78 ± 9.33 to 137 ± 21.70 particles kg-1, mostly white and ranging in size from 500-1000 µm. The prevalent types were: fragments (48%) > films (22%) > fibers (15%) > granules and lines (both 9%). Fourier transform mid-IR and near-IR spectra (FT-MIR-NIR) analysis registered terephthalate (48%), polypropylene (20%), polyethylene (17%), and polystyrene (15%) in all samples. These results contribute to the MP's pollution knowledge in sea salts to understand and reduce this significant human exposure route and environmental pollution source in the future.