Regional cerebral blood flow imaging assessment of brain function reconstruction in elderly hemiplegia patients by body weight support treadmill training

The mechanism underlying body weight support treadmill training in elderly hemiplegic stroke patients is largely unknown. This study aimed to elucidate the changes of cortical blood flow in seven elderly patients with post-stroke hemiplegia before and after body weight support treadmill training by semi-quantitative analysis of regional cerebral blood flow assessed by single photon emission computed tomography. Body weight support treadmill training for 6 months was effective in improving cerebral blood flow and promoting the walking speed and balance recovery in elderly patients with post-stroke hemiplegia.

Analyzing Sequential Patterns in Retail Databases

Finding correlated sequential patterns in large sequence databases is one of the essential tasks in data mining since a huge number of sequential patterns are usually mined, but it is hard to find sequential patterns with the correlation. According to the requirement of real applications, the needed data analysis should be different. In previous mining approaches, after mining the sequential patterns, sequential patterns with the weak affinity are found even with a high minimum support. In this paper, a new framework is suggested for mining weighted support affinity patterns in which an objective measure, sequential ws-confidence is developed to detect correlated sequential patterns with weighted support affinity patterns. To efficiently prune the weak affinity patterns, it is proved that ws-confidence measure satisfies the anti-monotone and cross weighted support properties which can be applied to eliminate sequential patterns with dissimilar weighted support levels. Based on the framework, a weighted support affinity pattern mining algorithm （WSMiner） is suggested. The performance study shows that WSMiner is efficient and scalable for mining weighted support affinity patterns.

Design Study of a Cable-based Gait Training Machine

This paper deals with a design approach of a gait training machine based on a quantitative gait analysis. The proposed training machine is composed of a body weight support device and a cable-driven parallel robot. This paper is focused on the cable-driven robot, which controls the pose of the lower limb through an orthosis placed on the patient＇s leg. The cable robot reproduces a normal gait movement through the motion of the orthosis. A motion capture system is used to perform the quantitative analysis of a normal gait, which will be used as an input to the inverse dynamic model of the cable robot. By means of an optimization algorithm, the optimal design parameters, which minimize the tensions in the cables, are determined. Two constraints are considered, i.e., a non-negative tension in the cables at all times, and a free cable/end-effector collision. Once the optimal solution is computed, a power analysis is carried out in order to size the robot actuators. The proposed approach can be easily extended for the design study of a similar type of cable robots.

Finite Projective Geometries and Classification of the Weight Hierarchies of Codes(Ⅰ)

The weight hierarchy of a binary linear [n, k] code C is the sequence (d 1, d 2, . . . , d k ), where d r is the smallest support of an r-dimensional subcode of C. The codes of dimension 4 are collected in classes and the possible weight hierarchies in each class is determined by finite projective geometries. The possible weight hierarchies in class A, B, C, D are determined in Part (I). The possible weight hierarchies in class E, F, G, H, I are determined in Part (II).

The Effect of Saddle-Assistive Device on Improving the Gait Parameters of Patients with the Lower Limbs Weakness:A Pilot Study

To help walking,using assistive devices can be considered to reduce the loads caused by weight and to effectively decrease the propulsive forces.In this study,a mobility Saddle-Assistive Device(S-AD)supporting body weight while walking was evaluated on two healthy volunteers.This device is based on the support of body weight against gravity with the help of a saddle,which is not used in other passive mobility assistive devices.To prove the efficiency of this device,the experimental results obtained while walking with this device were compared with those related to walking without the assistive device.The results showed that this device could significantly reduce the forces and torque of the lower and upper limbs when walking.By distributing the load on the saddle,the vertical force and the propulsive force in the best conditions were decreased to 46.7%and were increased to 13.7%in body weight,respectively.Using a S-AD can help patients with lower limbs weakness and elderly people to walk.

Personalised medicine with multiple treatments: a PhD thesis abstract

When there is substantial heterogeneity of treatment effectiveness for comparative treatmentselection, it is crucial to identify individualised treatment rules for patients who have heterogeneous responses to treatment. Existing approaches include directly modelling clinical outcomeby defining the optimal treatment rule according to the interactions between treatment andcovariates and outcome weighted approach that uses clinical outcome as weights to maximise atarget function whose value directly reflects correct treatment assignment. All existing articles ofestimating individualised treatment rules are all assuming just two treatment assignments. Herewe propose an outcome weighted learning approach that uses a vector hinge loss to extend estimating individualised treatment rules in multi-category treatments case. The consistency of theresulting estimator is shown. We also demonstrate the performance of our approach in simulationstudies and a real data analysis.