Discrimination between Alzheimer's disease and mild cognitive impairment using SOM and PSO-SVM.

In this study, an MRI-based classification framework was proposed to distinguish the patients with AD and MCI from normal participants by using multiple features and different classifiers. First, we extracted features (volume and shape) from MRI data by using a series of image processing steps. Subsequently, we applied principal component analysis (PCA) to convert a set of features of possibly correlated variables into a smaller set of values of linearly uncorrelated variables, decreasing the dimensions of feature space. Finally, we developed a novel data mining framework in combination with support vector machine (SVM) and particle swarm optimization (PSO) for the AD/MCI classification. In order to compare the hybrid method with traditional classifier, two kinds of classifiers, that is, SVM and a self-organizing map (SOM), were trained for patient classification. With the proposed framework, the classification accuracy is improved up to 82.35% and 77.78% in patients with AD and MCI. The result achieved up to 94.12% and 88.89% in AD and MCI by combining the volumetric features and shape features and using PCA. The present results suggest that novel multivariate methods of pattern matching reach a clinically relevant accuracy for the a priori prediction of the progression from MCI to AD.

Reliability and validity of a physical capacity evaluation used to assess individuals with intellectual disabilities and mental illness.

Physical capacity evaluations (PCEs) are important and frequently offered services in work practice. This study to investigate the reliability and validity of the National Taiwan University Hospital Physical Capacity Evaluation (NTUH PCE) on a sample of 149 participants consisted of three groups: 45 intellectual disability (ID), 56 mental illness (MI), and 48 no disability (ND). Intraclass correlation coefficient (ICC), Cronbach alpha, and one-way ANOVA were calculated where appropriate. Results indicated that most subtests of the NTUH PCE had good to excellent test-retest reliability (ICC, 0.75-0.95), with the exception of subtests of the position tolerance section for ID and MI groups and the hand coordination section for the ND group. Good internal consistency was shown on strength, mobility, and hand coordination sections (alpha, 0.96, 0.90, and 0.95, respectively), with the exception of the position tolerance section (alpha=0.37). The known group validity of the NTUH PCE in people with disabilities was satisfactory. In conclusion, although some improvements are needed in some subtests, the NTUH PCE is suitable for measuring physical work-related abilities of people with disabilities.

The application of the movement classification system in the diagnosis of children with Cerebral Palsy.

Cerebral Palsy is mean damage to the brain, causing non-progressive brain injury, such as hemiplegia, limbs palsy, epilepsy, involuntary movements, poor coordination. This paper proposes a movement evaluation and classification system, in view Cerebral Palsy children hand movement smoothness evaluation. In addition, the application of the movement classification system in the diagnosis of children with cerebral palsy is also discussed. The system contains: image capture, image segmentation, and information classification processing. Momentum analysis parameters and coordination neural network are used to conduct the data classification. The experimental results are shown that the proposed system has the higher accurate diagnostic rate of children are divided into cerebral palsy groups or normal groups.

Psychometric study of the test of variables of attention: preliminary findings on Taiwanese children with attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) is a common mental disorder in children. Unfortunately, reliable means of measuring attention and impulsivity to help with diagnoses are scarce. The test of variables of attention (TOVA) is a computer-administered continuous performance test measuring attention and impulsivity, designed to avoid confounding arising from language processing skills or short-term memory problems. Some evidence has indicated the TOVA can be useful in diagnosing ADHD. This study examines its validity and reliability in helping diagnose Taiwanese ADHD children. The study included 31 ADHD children (24 males, seven females) from a northern Taiwan children's hospital and 30 normal controls (18 males, 12 females) from the local community. The TOVA and the Child Behavior Checklist (CBCL) were administered to all children. TOVA scores for omissions, commissions, response time, response time variability, D' and ADHD scores were analyzed. Results showed a mean internal consistency of 0.81 for all six TOVA variables across conditions, with moderate convergent and discriminant validities. Groups showed significant differences in response time variability, D' and ADHD scores, with the normal group outperforming the ADHD group. Significant group differences were also found in all CBCL subscale scores except somatic complaints. The ADHD group obtained a clinically significant score on the hyperactivity subscale of the CBCL. The findings partially support the usefulness of the TOVA in assessing attention and impulsivity problems for a Taiwanese sample. Future studies should increase the sample size, use multiple measures, and collect behavior ratings from both parents and teachers.

The development and application of the telemedicine system in psychiatric counseling.

Telemedicine are the application and development of the telecommunication networks. In this study, we try to develop the telemedicine system and to discuss the network application of this system in psychiatric counseling. The preliminary result of this study is that the telemedicine system is more effective than traditional consultation and it can provide teleconsultation service for clients with depression through the internet.