A Computer Vision Framework For Finger-Tapping Evaluation In Parkinson's Disease

Objective: To define and evaluate a Computer-Vision (CV) method for scoring Paced Finger-Tapping (PFT) in Parkinson's disease (PD) using quantitative motion analysis of index-fingers and to compare the obtained scores to the UPDRS (Unified Parkinson's Disease Rating Scale) finger-taps (FT). Background: The naked-eye evaluation of PFT in clinical practice results in coarse resolution to determine PD status. Besides, sensor mechanisms for PFT evaluation may cause patients discomfort. In order to avoid cost and effort of applying wearable sensors, a CV system for non-invasive PFT evaluation is introduced. Methods: A database of 221 PFT videos from 6 PD patients was processed. The subjects were instructed to position their hands above their shoulders besides the face and tap the index-finger against the thumb consistently with speed. They were facing towards a pivoted camera during recording. The videos were rated by two clinicians between symptom levels 0-to-3 using UPDRS-FT. The CV method incorporates a motion analyzer and a face detector. The method detects the face of testee in each video-frame. The frame is split into two images from face-rectangle center. Two regions of interest are located in each image to detect index-finger motion of left and right hands respectively. The tracking of opening and closing phases of dominant hand index-finger produces a tapping time-series. This time-series is normalized by the face height. The normalization calibrates the amplitude in tapping signal which is affected by the varying distance between camera and subject (farther the camera, lesser the amplitude). A total of 15 features were classified using K-nearest neighbor (KNN) classifier to characterize the symptoms levels in UPDRS-FT. The target ratings provided by the raters were averaged. Results: A 10-fold cross validation in KNN classified 221 videos between 3 symptom levels with 75% accuracy. An area under the receiver operating characteristic curves of 82.6% supports feasibility of the obtained features to replicate clinical assessments. Conclusions: The system is able to track index-finger motion to estimate tapping symptoms in PD. It has certain advantages compared to other technologies (e.g. magnetic sensors, accelerometers etc.) for PFT evaluation to improve and automate the ratings

User perspectives on the Swedish Maternal Health Care Register

Background: Established in 1999, the Swedish Maternal Health Care Register (MHCR) collects data on pregnancy, birth, and the postpartum period for most pregnant women in Sweden. Antenatal care (ANC) midwives manually enter data into the Web-application that is designed for MHCR. The aim of this study was to investigate midwives? experiences, opinions and use of the MHCR. Method: A national, cross-sectional, questionnaire survey, addressing all Swedish midwives working in ANC, was conducted January to March 2012. The questionnaire included demographic data, preformed statements with six response options ranging from zero to five (0 = totally disagree and 5 = totally agree), and opportunities to add information or further clarification in the form of free text comments. Parametric and non-parametric methods and logistic regression analyses were applied, and content analysis was used for free text comments. Results: The estimated response rate was 53.1%. Most participants were positive towards the Web-application and the included variables in the MHCR. Midwives exclusively engaged in patient-related work tasks perceived the register as burdensome (70.3%) and 44.2% questioned the benefit of the register. The corresponding figures for midwives also engaged in administrative supervision were 37.8% and 18.5%, respectively. Direct electronic transfer of data from the medical records to the MHCR was emphasised as significant future improvement. In addition, the midwives suggested that new variables of interest should be included in the MHCR ? e.g., infertility, outcomes of previous pregnancy and birth, and complications of the index pregnancy. Conclusions: In general, the MHCR was valued positively, although perceived as burdensome. Direct electronic transfer of data from the medical records to the MHCR is a prioritized issue to facilitate the working situation for midwives. Finally, the data suggest that the MHCR is an underused source for operational planning and quality assessment in local ANC centres.