Feature extraction method for clock drawing test

Recently, the number of elderly persons with dementia has been increasing. In the past, we proposed a dementia evaluation system using daily conversations and developed the system with a conversational robot. However, the current system is not ready for practical use because it can only evaluate time/geographical orientation and short-term memory, and some methods to evaluate other orientations and functions is required as well. In this paper, we discuss a new dementia evaluation system using not only daily conversations but also drawing tests. The authors employed a Clock Drawing Test (CDT) as a new dementia evaluation test and implemented it in a tablet device. This paper discusses a feature extraction and recognition method to distinguish normal cases from dementia cases. After evaluation experiments, the proposed method could recognize 87.6% of the clock drawing images

Dementia detection using weighted direction index histograms and SVM for clock drawing test

AbstractIncreasing the number of elderly persons who have dementia is one of the severe social problems. In Japan, the Ministry of Health, Labor and Welfare expects that the number of dementia patients will be around 5 million in 2025. It is also easily estimated that they require various living supports. Therefore, early detection and prevention of dementia are important. The authors have been developing a new system for quantitative and accurate evaluation of dementia. The basic concept of our system is evaluating a patient's dementia types and progression without awareness. To realize this, we are now developing the system using daily conversations, drawings, facial expressions and so on. In this paper, we focused on Clock Drawing Test (CDT) and proposed a dementia evaluation method for CDT. In the proposed method, Weighted Direction Index Histogram Method was used to extract features from given images, and Support Vector Machine (SVM) detected dementia cases from them. As a result of evaluation experiments, the proposed method could detect 97.1% of dementia cases correctly

Differentiation Between Dementia With Lewy Bodies And Alzheimer’s Disease Using Voxel-Based Morphometry Of Structural MRI:AMulticenter Study

Dementia with Lewy bodies (DLB) is one of the main etiologies of neurodegenerative dementia after Alzheimer’s disease (AD).1 Distinguishing DLB from AD is difficult because of their overlapping clinical and pathological features.2–4 Patients with clinically defined DLB may also have AD-type pathological changes as well as the characteristic Lewy bodies. However, the differential diagnosis is particularly important because DLB respond better to cholinesterase inhibitors but are sensitive to neuroleptics, which cause worsening of clinical status