Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach

Purpose

Functional magnetic resonance imaging (fMRI) in resting state can be used to evaluate the functional organization of the human brain in the absence of any task or stimulus. The functional connectivity (FC) has non-stationary nature and consented to be varying over time. By considering the dynamic characteristics of the FC and using graph theoretical analysis and a machine learning approach, we aim to identify the laterality in cases of temporal lobe epilepsy (TLE).

Methods

Six global graph measures are extracted from static and dynamic functional connectivity matrices using fMRI data of 35 unilateral TLE subjects. Alterations in the time trend of the graph measures are quantified. The random forest (RF) method is used for the determination of feature importance and selection of dynamic graph features including mean, variance, skewness, kurtosis, and Shannon entropy. The selected features are used in the support vector machine (SVM) classifier to identify the left and right epileptogenic sides in patients with TLE.

Results

Our results for the performance of SVM demonstrate that the utility of dynamic features improves the classification outcome in terms of accuracy (88.5% for dynamic features compared with 82% for static features). Selecting the best dynamic features also elevates the accuracy to 91.5%.

Conclusion

Accounting for the non-stationary characteristics of functional connectivity, dynamic connectivity analysis of graph measures along with machine learning approach can identify the temporal trend of some specific network features. These network features may be used as potential imaging markers in determining the epileptogenic hemisphere in patients with TLE.

     

The first presentation of Wolcott‐Rallison syndrome in a four‐month‐old infant with diabetic ketoacidosis (DKA) precipitating by COVID‐19: A case report

Monogenic diabetes mellitus (eg, Wolcott‐Rallison syndrome) is a rare condition. It associates with neonatal or early‐infancy insulin‐dependent diabetes. We reported DKA in the four‐month infant as the first presentation of monogenic diabetes that has accelerated by COVID‐19 infection. Therefore, considering the concurrency of COVID‐19 and DKA is crucial.     

Design,construction, and evaluation of “sensor lock”: an electromechanical stance control knee joint

Background and aim: Most currently-available stance control knee ankle foot orthoses (SCKAFOs) still need full knee extension to lock the knee joint, and they are still noisy, bulky, and heavy. Therefore, the aim of this study was to design, construct, and evaluate an original electromechanical SCKAFO knee joint that could feasibly solve these problems, and thus address the problems of current stance control knee joints with regards to their structure, function, cosmesis, and cost.

Method: Ten able-bodied (AB) participants and two (knee ankle foot orthosis) KAFO users were recruited to participate in the study. A custom SCKAFO with the same set of components was constructed for each participant. Lower limb kinematics were captured using a 6-camera, video-based motion analysis system.

Results: For AB participants, significant differences were found between normal walking and walking with the SCKAFO for temporal-spatial parameters and between orthoses with two modes of knee joints in the healthy subjects. Walking with stance control mode produced greater walking speed and step length, greater knee flexion during swing, and less pelvic obliquity than walking with a locked knee, for both AB and KAFO users.

Conclusions: The feasibility of this new knee joint with AB people was demonstrated.

• Implications for rehabilitation

• Stance control knee ankle foot orthoses (SCKAFOs) are designed to stop knee flexion in stance phase and provide free knee movement during swing phase of walking.

• Due to their high cost, size, excessive weight, and poor performance, few SCKAFO were optimal clinically and commercially.

• The feasibility of the new knee joint with able-bodied people and poliomyelitis subjects was demonstrated.

     

Comparing Two Orthoses for Managing Medial Knee Osteoarthritis: Lateral Wedge with Subtalar Strap While Barefoot Versus Lateral Wedged Insole Fitted Within Sandal

BackgroundUsing foot orthoses for managing medial knee osteoarthritis (MKOA) is common, although its effectiveness is in debate. Most orthoses are placed inside the shoe as a lateral wedged insole. Thus, most studies in this area have focused on the effect of insoles used with shoes. This study compared the effects of a lateral wedge with subtalar strap (combined insole) used while barefoot and lateral wedged insole fitted within sandal on pain, function and external knee adduction moment (EKAM) in patients with MKOA to consider which orthotic treatment is better.MethodsIn this quasi-experimental pretest–posttest study, 29 participants with medial knee osteoarthritis were divided into two groups: (1) combined insole (n = 15) and (2) sandal (n = 14) groups. We recorded their gait while walking with and without orthoses using a motion analysis system. We evaluated their pain and performance with visual analog scale, Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire, 30 s chair stand, and Timed Up and Go functional tests. The pain and performance evaluations were repeated after one month.ResultsThe pain immediately decreased after walking with both orthoses (p < 0.001). There was no significant difference in EKAM results between the two orthoses. Pain and performance improved in both groups after a one month using the orthoses (p < 0.01).ConclusionBoth types of orthoses have similar effect and lead to better performance and less pain after 1 month.     

Kinematic and electromyography analysis of paraplegic gait with the assistance of mechanical orthosis and walker

Objective: To investigate the kinematics, functional sub-tasks, and excitation levels of the trunk and upper extremity muscles of paraplegic subjects during walker-assisted locomotion.Design: Retrospective cross-sectional study.Setting: Gait analysis laboratory.Participants: Eight individuals with spinal cord injury at T12, lower extremity motor score less than 4, and capable of walking independently with the assistance of ankle-foot orthosis and walker.Main Outcome Measures: Kinematics of pelvis, trunk, shoulder and elbow; trajectory of center of mass; and electromyography (EMG) activity of trunk and upper extremity muscles during gait.Results: Four subtasks were characterized for each locomotion step, based on the kinetics and kinematics data: (1) balance adjustment, (2) walker propulsion, (3) leg raising, and (4) leg swing. The latter two involved large lateral maneuvres by the trunk and pelvis and appeared to be the most skill- and muscle activity-demanding subtasks. The main muscles contributing into these subtasks were the ipsilateral paraspinal and abdominal muscles, as well as the contralateral scapulothoracic and shoulder girdle muscles, with EMG intensities significantly higher than their minimum mean intensities (P < 0.05) and those of the contralateral side (P < 0.05).Conclusions: Our results provide more insight into the functional sub-tasks and muscular demands of walker-assisted paraplegic gait that can help to design appropriate muscle strengthening programs, as well as developing more effective gait orthoses.