Description and Prediction of Freezing of Gait in Parkinson's Disease from Wearable Inertial Measurements Units

Parkinson's disease (PD) is a neuro-degenerative disorder, the second most common after Alzheimer's disease. After diagnosis, treatments can help to relieve the symptoms, but there is no known cure for PD. PD is characterized by a combination of motor and no-motor dysfunctions. Among the motor symptoms there is the so called Freezing of Gait (FoG). The FoG is a phenomenon in PD patients in which the feet stock to the floor and is difficult for the patient to initiate movement. FoG is a severe problem, since it is associated with falls, anxiety, loss of mobility, accidents, mortality and it has substantial clinical and social consequences decreasing the quality of life in PD patients. Medicine can be very successful in controlling movements disorders and dealing with some of the PD symptoms. However, the relationship between medication and the development of FoG remains unclear. Several studies have demonstrated that visual or auditory rhythmical cuing allows PD patients to improve their motor abilities. Rhythmic auditory stimulation (RAS) was shown to be particularly effective at improving gait, specially with patients that manifest FoG. While RAS allows to reduce the time and the effects of FoGs occurrence in PD patients after the FoG is detected, it can not avoid the episode due to the latency of detection. An improvement of the system would be the prediction of the FoG. This thesis was developed following two main objectives: (1) the finding of specifics properties during pre FoG periods different from normal walking context and other walking events like turns and stops using the information provided by the inertial measurements units (IMUs) and (2) the formulation of a model for automatically detect the pre FoG patterns in order to completely avoid the upcoming freezing event in PD patients. The first part focuses on the analysis of different methods for feature extraction which might lead in the FoG occurrence.

A novel, bedside technique to rapidly identify umbilical cord blood units with high total nucleated cell numbers

BACKGROUND With increasing demand for umbilical cord blood units (CBUs) with total nucleated cell (TNC) counts of more than 150 × 10(7) , preshipping assessment is mandatory. Umbilical cord blood processing requires aseptic techniques and laboratories with specific air quality and cleanliness. Our aim was to establish a fast and efficient method for determining TNC counts at the obstetric ward without exposing the CBU to the environment. STUDY DESIGN AND METHODS Data from a total of 151 cord blood donations at a single procurement site were included in this prospective study. We measured TNC counts in cord blood aliquots taken from the umbilical cord (TNCCord ), from placenta (TNCPlac ), and from a tubing segment of the sterile collection system (TNCTS ). TNC counts were compared to reference TNC counts in the CBU which were ascertained at the cord blood bank (TNCCBU ). RESULTS TNCTS counts (173 ± 33 × 10(7) cells; calculated for 1 unit) correlated fully with the TNCCBU reference counts (166 ± 33 × 10(7) cells, Pearson's r = 0.97, p < 0.0001). In contrast, TNCCord and TNCPlac counts were more disparate from the reference (r = 0.92 and r = 0.87, respectively). CONCLUSIONS A novel method of measuring TNC counts in tubing segments from the sterile cord blood collection system allows rapid and correct identification of CBUs with high cell numbers at the obstetric ward without exposing cells to the environment. This approach may contribute to cost efficacy as only CBUs with satisfactory TNC counts need to be shipped to the cord blood bank.

Homogeneous Spatial Units (HSU) - a Pan-European geographical basis for environmental and socio-economic modelling

The spatial data set delineates areas with similar environmental properties regarding soil, terrain morphology, climate and affiliation to the same administrative unit (NUTS3 or comparable units in size) at a minimum pixel size of 1km2. The scope of developing this data set is to provide a link between spatial environmental information (e.g. soil properties) and statistical data (e.g. crop distribution) available at administrative level. Impact assessment of agricultural management on emissions of pollutants or radiative active gases, or analysis regarding the influence of agricultural management on the supply of ecosystem services, require the proper spatial coincidence of the driving factors. The HSU data set provides e.g. the link between the agro-economic model CAPRI and biophysical assessment of environmental impacts (updating previously spatial units, Leip et al. 2008), for the analysis of policy scenarios. Recently, a statistical model to disaggregate crop information available from regional statistics to the HSU has been developed (Lamboni et al. 2016). The HSU data set consists of the spatial layers provided in vector and raster format as well as attribute tables with information on the properties of the HSU. All input data for the delineation the HSU is publicly available. For some parameters the attribute tables provide the link between the HSU data set and e.g. the soil map(s) rather than the data itself. The HSU data set is closely linked the USCIE data set.