Digital spiral analysis for objective assessment of fine motor timing variability in Parkinson's disease

OBJECTIVES: To develop a method for objective assessment of fine motor timing variability in Parkinson’s disease (PD) patients, using digital spiral data gathered by a touch screen device. BACKGROUND: A retrospective analysis was conducted on data from 105 subjects including65 patients with advanced PD (group A), 15 intermediate patients experiencing motor fluctuations (group I), 15 early stage patients (group S), and 10 healthy elderly subjects (HE) were examined. The subjects were asked to perform repeated upper limb motor tasks by tracing a pre-drawn Archimedes spiral as shown on the screen of the device. The spiral tracing test was performed using an ergonomic pen stylus, using dominant hand. The test was repeated three times per test occasion and the subjects were instructed to complete it within 10 seconds. Digital spiral data including stylus position (x-ycoordinates) and timestamps (milliseconds) were collected and used in subsequent analysis. The total number of observations with the test battery were as follows: Swedish group (n=10079), Italian I group (n=822), Italian S group (n = 811), and HE (n=299). METHODS: The raw spiral data were processed with three data processing methods. To quantify motor timing variability during spiral drawing tasks Approximate Entropy (APEN) method was applied on digitized spiral data. APEN is designed to capture the amount of irregularity or complexity in time series. APEN requires determination of two parameters, namely, the window size and similarity measure. In our work and after experimentation, window size was set to 4 and similarity measure to 0.2 (20% of the standard deviation of the time series). The final score obtained by APEN was normalized by total drawing completion time and used in subsequent analysis. The score generated by this method is hence on denoted APEN. In addition, two more methods were applied on digital spiral data and their scores were used in subsequent analysis. The first method was based on Digital Wavelet Transform and Principal Component Analysis and generated a score representing spiral drawing impairment. The score generated by this method is hence on denoted WAV. The second method was based on standard deviation of frequency filtered drawing velocity. The score generated by this method is hence on denoted SDDV. Linear mixed-effects (LME) models were used to evaluate mean differences of the spiral scores of the three methods across the four subject groups. Test-retest reliability of the three scores was assessed after taking mean of the three possible correlations (Spearman’s rank coefficients) between the three test trials. Internal consistency of the methods was assessed by calculating correlations between their scores. RESULTS: When comparing mean spiral scores between the four subject groups, the APEN scores were different between HE subjects and three patient groups (P=0.626 for S group with 9.9% mean value difference, P=0.089 for I group with 30.2%, and P=0.0019 for A group with 44.1%). However, there were no significant differences in mean scores of the other two methods, except for the WAV between the HE and A groups (P<0.001). WAV and SDDV were highly and significantly correlated to each other with a coefficient of 0.69. However, APEN was not correlated to neither WAV nor SDDV with coefficients of 0.11 and 0.12, respectively. Test-retest reliability coefficients of the three scores were as follows: APEN (0.9), WAV(0.83) and SD-DV (0.55). CONCLUSIONS: The results show that the digital spiral analysis-based objective APEN measure is able to significantly differentiate the healthy subjects from patients at advanced level. In contrast to the other two methods (WAV and SDDV) that are designed to quantify dyskinesias (over-medications), this method can be useful for characterizing Off symptoms in PD. The APEN was not correlated to none of the other two methods indicating that it measures a different construct of upper limb motor function in PD patients than WAV and SDDV. The APEN also had a better test-retest reliability indicating that it is more stable and consistent over time than WAV and SDDV.

Är variation i STFI-tjocklek ett bra mått på kartongs bulighet? : Are variation in STFI-thickness a good measure of uneven surface, bumpiness, on cardboard?

This degree project aim to evaluate if variations of the STFI thickness can be used to assess bumpiness on cardboard. During the project cardboard samples were measured using Bendtsen, PPS, a L&W formation tester, OptiTopo, Ambertec formation, the STFI thickness tester and a visual comparison. The different methods were then compared to see if there is any correlations between them. The results showed that the visual comparison and OptiTopo correlates. The STFI thickness tester shows however no correlation with the OptiTopo and visual comparison, thus aren't suitable measuring bumpiness.

Distance measure and the p-median problem in rural areas

The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

What is important for you? A qualitative interview study of living with diabetes and experiences of diabetes care to establish a basis for a tailored Patient-Reported Outcome Measure for the Swedish National Diabetes Register

OBJECTIVES: There is a growing emphasis on the perspective of individuals living with diabetes and the need for a more person-centred diabetes care. At present, the Swedish National Diabetes Register (NDR) lacks patient-reported outcome measures (PROMs) based on the perspective of the patient. As a basis for a new PROM, the aim of this study was to describe important aspects in life for adult individuals with diabetes. DESIGN: Semistructured qualitative interviews analysed using content analysis. SETTING: Hospital-based outpatient clinics and primary healthcare clinics in Sweden. PARTICIPANTS: 29 adults with type 1 diabetes mellitus (DM) (n=15) and type 2 DM (n=14). INCLUSION CRITERIA: Swedish adults (≥18 years) living with type 1 DM or type 2 DM (duration ≥5 years) able to describe their situation in Swedish. Purposive sampling generated heterogeneous characteristics. RESULTS: To live a good life with diabetes is demanding for the individual, but experienced barriers can be eased by support from others in the personal sphere, and by professional support from diabetes care. Diabetes care was a crucial resource to nurture the individual's ability and knowledge to manage diabetes, and to facilitate life with diabetes by supplying support, guidance, medical treatment and technical devices tailored to individual needs. The analysis resulted in the overarching theme 'To live a good life with diabetes' constituting the two main categories 'How I feel and how things are going with my diabetes' and 'Support from diabetes care in managing diabetes' including five different categories. CONCLUSIONS: Common aspects were identified including the experience of living with diabetes and support from diabetes care. These will be used to establish a basis for a tailored PROM for the NDR.