Data Mining in Clinical Practice for the Quantification of Motor Impairment in Parkinson's Disease

Advances in biomedical signal acquisition systems for motion analysis have led to lowcost and ubiquitous wearable sensors which can be used to record movement data in different settings. This implies the potential availability of large amounts of quantitative data. It is then crucial to identify and to extract the information of clinical relevance from the large amount of available data. This quantitative and objective information can be an important aid for clinical decision making. Data mining is the process of discovering such information in databases through data processing, selection of informative data, and identification of relevant patterns. The databases considered in this thesis store motion data from wearable sensors (specifically accelerometers) and clinical information (clinical data, scores, tests). The main goal of this thesis is to develop data mining tools which can provide quantitative information to the clinician in the field of movement disorders. This thesis will focus on motor impairment in Parkinson's disease (PD). Different databases related to Parkinson subjects in different stages of the disease were considered for this thesis. Each database is characterized by the data recorded during a specific motor task performed by different groups of subjects. The data mining techniques that were used in this thesis are feature selection (a technique which was used to find relevant information and to discard useless or redundant data), classification, clustering, and regression. The aims were to identify high risk subjects for PD, characterize the differences between early PD subjects and healthy ones, characterize PD subtypes and automatically assess the severity of symptoms in the home setting.

Analisi dell’influenza dei moti rigidi di una trattrice agricola sulle vibrazioni a corpo intero trasmesse all’operatore

L’esposizione degli operatori in campo agricolo alle vibrazioni trasmesse al corpo intero, produce effetti dannosi alla salute nel breve e nel lungo termine. Le vibrazioni che si generano sulle trattrici agricole hanno una elevata intensità e una bassa frequenza. Le componenti orizzontali, amplificate dalla posizione elevata della postazione di guida dall’asse di rollio, presentano maggiori criticità per quanto riguarda i sistemi di smorzamento rispetto alle componenti verticali. Queste caratteristiche rendono difficoltosa la progettazione dei sistemi dedicati alla riduzione del livello vibrazionale per questa categoria di macchine agricole. Nonostante l’installazione di diversi sistemi di smorzamento, il livello di vibrazioni a cui è sottoposto l’operatore può superare, in diverse condizioni di impiego, i livelli massimi imposti dalla legge per la salvaguardia della salute. L’obiettivo di questo lavoro è quello di valutare l’influenza dei moti rigidi di una trattrice (beccheggio, rollio e saltellamento) dotata di sospensione assale anteriore, sospensione cabina e sospensione sedile, sul livello vibrazionale trasmesso all’operatore.E’ stata pertanto strumenta una trattrice con accelerometri e inclinometri installati su telaio, cabina e sedile e utilizzata in diverse condizioni di lavoro in campo e di trasporto su strada. Dall’analisi delle prove effettuate emerge che durante il trasporto su strada è predominante l’accelerazione longitudinale, a causa dell’elevata influenza del beccheggio. La sospensione riduce notevolmente il moto rigido di beccheggio mentre l’effetto della sospensione della cabina è quello di incrementare, in ogni condizione di lavoro, il livello di accelerazione trasmesso dal telaio della macchina.

Risk analysis of tractor rollover in the normal operation in field

Tractor rollover represent a primary cause of death or serious injury in agriculture and despite the mandatory Roll-Over Protective Structures (ROPS), that reduced the number of injuries, tractor accidents are still of great concern. Because of their versatility and wide use many studies on safety are concerned with the stability of tractors, but they often prefer controlled tests or laboratory tests. The evaluation of tractors working in field, instead, is a very complex issue because the rollover could be influenced by the interaction among operator, tractor and environment. Recent studies are oriented towards the evaluation of the actual working conditions developing prototypes for driver assistance and data acquisition. Currently these devices are produced and sold by manufacturers. A warning device was assessed in this study with the aim to evaluate its performance and to collect data on different variables influencing the dynamics of tractors in field by monitoring continuously the working conditions of tractors operating at the experimental farm of the Bologna University. The device consists of accelerometers, gyroscope, GSM/GPRS, GPS for geo-referencing and a transceiver for the automatic recognition of tractor-connected equipment. A microprocessor processes data and provides information, through a dedicated algorithm requiring data on the geometry of the tested tractor, on the level of risk for the operator in terms of probable loss of stability and suggests corrective measures to reduce the potential instability of the tractor.

Design and implementation of a 3D computer game controller using inertial MEMS sensors

Though 3D computer graphics has seen tremendous advancement in the past two decades, most available mechanisms for computer interaction in 3D are high cost and targeted for industry and virtual reality applications. Recent advances in Micro-Electro-Mechanical-System (MEMS) devices have brought forth a variety of new low-cost, low-power, miniature sensors with high accuracy, which are well suited for hand-held devices. In this work a novel design for a 3D computer game controller using inertial sensors is proposed, and a prototype device based on this design is implemented. The design incorporates MEMS accelerometers and gyroscopes from Analog Devices to measure the three components of the acceleration and angular velocity. From these sensor readings, the position and orientation of the hand-held compartment can be calculated using numerical methods. The implemented prototype is utilizes a USB 2.0 compliant interface for power and communication with the host system. A Microchip dsPIC microcontroller is used in the design. This microcontroller integrates the analog to digital converters, the program memory flash, as well as the core processor, on a single integrated circuit. A PC running Microsoft Windows operating system is used as the host machine. Prototype firmware for the microcontroller is developed and tested to establish the communication between the design and the host, and perform the data acquisition and initial filtering of the sensor data. A PC front-end application with a graphical interface is developed to communicate with the device, and allow real-time visualization of the acquired data.

Comparison of modal analysis results of laser vibrometry and nearfield acoustical holography measurements of an aluminum plate

Noise and vibration has long been sought to be reduced in major industries: automotive, aerospace and marine to name a few. Products must be tested and pass certain levels of federally regulated standards before entering the market. Vibration measurements are commonly acquired using accelerometers; however limitations of this method create a need for alternative solutions. Two methods for non-contact vibration measurements are compared: Laser Vibrometry, which directly measures the surface velocity of the aluminum plate, and Nearfield Acoustic Holography (NAH), which measures sound pressure in the nearfield, and using Green’s Functions, reconstructs the surface velocity at the plate. The surface velocity from each method is then used in modal analysis to determine the comparability of frequency, damping and mode shapes. Frequency and mode shapes are also compared to an FEA model. Laser Vibrometry is a proven, direct method for determining surface velocity and subsequently calculating modal analysis results. NAH is an effective method in locating noise sources, especially those that are not well separated spatially. Little work has been done in incorporating NAH into modal analysis.

Effectiveness of a nondestructive evaluation technique for assessing standing timber quality

The research presented in this thesis was conducted to further the development of the stress wave method of nondestructively assessing the quality of wood in standing trees. The specific objective of this research was to examine, in the field, use of two stress wave nondestructive assessment techniques. The first technique examined utilizes a laboratory-built measurement system consisting of commercially available accelerometers and a digital storage oscilloscope. The second technique uses a commercially available tool that incorporates several technologies to determine speed of stress wave propagation in standing trees. Field measurements using both techniques were conducted on sixty red pine trees in south-central Wisconsin and 115 ponderosa pine trees in western Idaho. After in-situ measurements were taken, thirty tested red pine trees were felled and a 15-foot-long butt log was obtained from each tree, while all tested ponderosa pine trees were felled and an 8 1/2 -foot-long butt log was obtained, respectively. The butt logs were sent to the USDA Forest Products Laboratory and nondestructively tested using a resonance stress wave technique. Strong correlative relationships were observed between stress wave values obtained from both field measurement techniques. Excellent relationships were also observed between standing tree and log speed-of-sound values.

Study of accelerometer assisted single key positioning user input systems

New designs of user input systems have resulted from the developing technologies and specialized user demands. Conventional keyboard and mouse input devices still dominate the input speed, but other input mechanisms are demanded in special application scenarios. Touch screen and stylus input methods have been widely adopted by PDAs and smartphones. Reduced keypads are necessary for mobile phones. A new design trend is exploring the design space in applications requiring single-handed input, even with eyes-free on small mobile devices. This requires as few keys on the input device to make it feasible to operate. But representing many characters with fewer keys can make the input ambiguous. Accelerometers embedded in mobile devices provide opportunities to combine device movements with keys for input signal disambiguation. Recent research has explored its design space for text input. In this dissertation an accelerometer assisted single key positioning input system is developed. It utilizes input device tilt directions as input signals and maps their sequences to output characters and functions. A generic positioning model is developed as guidelines for designing positioning input systems. A calculator prototype and a text input prototype on the 4+1 (5 positions) positioning input system and the 8+1 (9 positions) positioning input system are implemented using accelerometer readings on a smartphone. Users use one physical key to operate and feedbacks are audible. Controlled experiments are conducted to evaluate the feasibility, learnability, and design space of the accelerometer assisted single key positioning input system. This research can provide inspiration and innovational references for researchers and practitioners in the positioning user input designs, applications of accelerometer readings, and new development of standard machine readable sign languages.

Investigation of the effect of using data collection technology on students' attitudes to science instruction

The purpose of this project was to investigate the effect of using of data collection technology on student attitudes towards science instruction. The study was conducted over the course of two years at Madison High School in Adrian, Michigan, primarily in college preparatory physics classes, but also in one college preparatory chemistry class and one environmental science class. A preliminary study was conducted at a Lenawee County Intermediate Schools student summer environmental science day camp. The data collection technology used was a combination of Texas Instruments TI-84 Silver Plus graphing calculators and Vernier LabPro data collection sleds with various probeware attachments, including motion sensors, pH probes and accelerometers. Students were given written procedures for most laboratory activities and were provided with data tables and analysis questions to answer about the activities. The first year of the study included a pretest and posttest measuring student attitudes towards the class they were enrolled in. Pre-test and post-test data were analyzed to determine effect size, which was found to be very small (Coe, 2002). The second year of the study focused only on a physics class and used Keller’s ARCS model for measuring student motivation based on the four aspects of motivation: Attention, Relevance, Confidence and Satisfaction (Keller, 2010). According to this model, it was found that there were two distinct groups in the class, one of which was motivated to learn and the other that was not. The data suggest that the use of data collection technology in science classes should be started early in a student’s career, possibly in early middle school or late elementary. This would build familiarity with the equipment and allow for greater exploration by the student as they progress through high school and into upper level science courses.

Accelerometer based measurements of combustion in an automotive turbocharged diesel engine

The capability to detect combustion in a diesel engine has the potential of being an important control feature to meet increasingly stringent emission regulations, develop alternative combustion strategies, and use of biofuels. In this dissertation, block mounted accelerometers were investigated as potential feedback sensors for detecting combustion characteristics in a high-speed, high pressure common rail (HPCR), 1.9L diesel engine. Accelerometers were positioned in multiple placements and orientations on the engine, and engine testing was conducted under motored, single and pilot-main injection conditions. Engine tests were conducted at varying injection timings, engine loads, and engine speeds to observe the resulting time and frequency domain changes of the cylinder pressure and accelerometer signals. The frequency content of the cylinder pressure based signals and the accelerometer signals between 0.5 kHz and 6 kHz indicated a strong correlation with coherence values of nearly 1. The accelerometers were used to produce estimated combustion signals using the Frequency Response Functions (FRF) measured from the frequency domain characteristics of the cylinder pressure signals and the response of the accelerometers attached to the engine block. When compared to the actual combustion signals, the estimated combustion signals produced from the accelerometer response had Root Mean Square Errors (RMSE) between 7% and 25% of the actual signals peak value. Weighting the FRF’s from multiple test conditions along their frequency axis with the coherent output power reduced the median RMSE of the estimated combustion signals and the 95th percentile of RMSE produced from each test condition. The RMSE’s of the magnitude based combustion metrics including peak cylinder pressure, MPG, peak ROHR, and work estimated from the combustion signals produced by the accelerometer responses were between 15% and 50% of their actual value. The MPG measured from the estimated pressure gradient shared a direct relationship to the actual MPG. The location based combustion metrics such as the location of peak values and burn durations were capable of RMSE measurements as low as 0.9°. Overall, accelerometer based combustion sensing system was capable of detecting combustion and providing feedback regarding the in cylinder combustion process

Ethnic Minority Children’s Active Commuting to School and Association with Physical Activity and Pedestrian Safety Behaviors

Background: Children's active commuting to school, i.e. walking or cycling to school, was associated with greater moderate-to-vigorous physical activity, although studies among ethnic minorities are sparse. Objectives: Among a low-income, ethnic minority sample of fourth grade students from eight public schools, we examined (1) correlates of active commuting to school and (2) the relationship between active commuting to school and moderate-to-vigorous physical activity. Methods: We conducted a cross-sectional analysis of baseline measurements from a sample of participants (n=149) aged 9-12 years from a walk to school intervention study in Houston, Texas. The primary outcome was the weekly rate of active commuting to school. Daily moderate-to-vigorous physical activity, measured by accelerometers, was a secondary outcome. Child self-efficacy (alpha=0.75), parent self-efficacy (alpha=0.88), and parent outcome expectations (alpha=0.78) were independent variables. Participant characteristics (age, gender, race/ethnicity, distance from home to school, acculturation, and BMI percentile) were independent sociodemographic variables. We used mixed-model regression analyses to account for clustering by school and a stepwise procedure with backward elimination of non-significant interactions and covariates to identify significant moderators and predictors. School-level observations of student pedestrians were assessed and compared using chi-square tests of independence. Results: Among our sample, which was 61.7% Latino, the overall rate of active commuting to school was 43%. In the mixed model for active commuting to school, parent self-efficacy (std. beta = 0.18, p=0.018) and age (std. beta = 0.18, p=0.018) were positively related. Latino students had lower rates of active commuting to school than non-Latinos ( 16.5%, p=0.040). Distance from home to school was inversely related to active commuting to school (std. beta = 0.29, p<0.001). In the mixed model for moderate-to-vigorous physical activity, active commuting to school was positively associated (std. beta = 0.31, p <0.001). Among the Latino subsample, child acculturation was negatively associated with active commuting to school (std. beta = -0.23, p=0.01). With regard to school-level pedestrian safety observations, 37% of students stopped at the curb and 2.6% looked left-right-left before crossing the street. Conclusion: Although still below national goals, the rate of active commuting was relatively high, while the rate of some pedestrian safety behaviors was low among this low-income, ethnic minority population. Programs and policies to encourage safe active commuting to school are warranted and should consider the influence of parents, acculturation, and ethnicity.

Intra-session test-retest reliability of pelvic floor muscle electromyography during running

INTRODUCTION AND HYPOTHESIS The prevalence of female stress urinary incontinence is high, and young adults are also affected, including athletes, especially those involved in "high-impact" sports. To date there have been almost no studies testing pelvic floor muscle (PFM) activity during dynamic functional whole body movements. The aim of this study was the description and reliability test of PFM activity and time variables during running. METHODS A prospective cross-sectional study including ten healthy female subjects was designed with the focus on the intra-session test-retest reliability of PFM activity and time variables during running derived from electromyography (EMG) and accelerometry. RESULTS Thirteen variables were identified based on ten steps of each subject: Six EMG variables showed good reliability (ICC 0.906-0.942) and seven time variables did not show good reliability (ICC 0.113-0.731). Time variables (e.g. time difference between heel strike and maximal acceleration of vaginal accelerator) showed low reliability. However, relevant PFM EMG variables during running (e.g., pre-activation, minimal and maximal activity) could be identified and showed good reliability. CONCLUSION Further adaptations regarding measurement methods should be tested to gain better control of the kinetics and kinematics of the EMG probe and accelerometers. To our knowledge this is the first study to test the reliability of PFM activity and time variables during dynamic functional whole body movements. More knowledge of PFM activity and time variables may help to provide a deeper insight into physical strain with high force impacts and important functional reflexive contraction patterns of PFM to maintain or to restore continence.

Regional differences of physical activity and sedentary behaviour in Swiss children are not explained by socio-demographics or the built environment

Objective We evaluated whether regional differences in physical activity (PA) and sedentary behaviour (SB) existed along language boundaries within Switzerland and whether potential differences would be explained by socio-demographics or environmental characteristics. Methods We combined data of 611 children aged 4 to 7 years from four regional studies. PA and SB were assessed by accelerometers. Information about the socio-demographic background was obtained by questionnaires. Objective neighbourhood attributes could be linked to home addresses. Multivariate regression models were used to test associations between PA and SB and socio-demographic characteristics and neighbourhood attributes. Results Children from the German compared to the French-speaking region were more physically active and less sedentary (by 10–15 %, p < 0.01). Although German-speaking children lived in a more favourable environment and a higher socioeconomic neighbourhood (differences p < 0.001), these characteristics did not explain the differences in PA behaviour between French and German speaking. Conclusions Factors related to the language region, which might be culturally rooted were among the strongest correlates of PA and SB among Swiss children, independent of individual, social and environmental factors.

Analysis of behavioral changes in dairy cows associated with claw horn lesions

Detecting lame cows is important in improving animal welfare. Automated tools are potentially useful to enable identification and monitoring of lame cows. The goals of this study were to evaluate the suitability of various physiological and behavioral parameters to automatically detect lameness in dairy cows housed in a cubicle barn. Lame cows suffering from a claw horn lesion (sole ulcer or white line disease) of one claw of the same hind limb (n=32; group L) and 10 nonlame healthy cows (group C) were included in this study. Lying and standing behavior at night by tridimensional accelerometers, weight distribution between hind limbs by the 4-scale weighing platform, feeding behavior at night by the nose band sensor, and heart activity by the Polar device (Polar Electro Oy, Kempele, Finland) were assessed. Either the entire data set or parts of the data collected over a 48-h period were used for statistical analysis, depending upon the parameter in question. The standing time at night over 12 h and the limb weight ratio (LWR) were significantly higher in group C as compared with group L, whereas the lying time at night over 12 h, the mean limb difference (△weight), and the standard deviation (SD) of the weight applied on the limb taking less weight were significantly lower in group C as compared with group L. No significant difference was noted between the groups for the parameters of heart activity and feeding behavior at night. The locomotion score of cows in group L was positively correlated with the lying time and △weight, whereas it was negatively correlated with LWR and SD. The highest sensitivity (0.97) for lameness detection was found for the parameter SD [specificity of 0.80 and an area under the curve (AUC) of 0.84]. The highest specificity (0.90) for lameness detection was present for Δweight (sensitivity=0.78; AUC=0.88) and LWR (sensitivity=0.81; AUC=0.87). The model considering the data of SD together with lying time at night was the best predictor of cows being lame, accounting for 40% of the variation in the likelihood of a cow being lame (sensitivity=0.94; specificity=0.80; AUC=0.86). In conclusion, the data derived from the 4-scale-weighing platform, either alone or combined with the lying time at night over 12 h, represent the most valuable parameters for automated identification of lame cows suffering from a claw horn lesion of one individual hind limb.

Exploring the association of children's engagement in nature and outdoor activity with physical activity: A systematic review

The natural environment and green spaces are settings that may facilitate physical activity and, as a result, combat childhood obesity and benefit children's physical health. A systematic review was conducted to assess the effect of children's engagement in outdoor activity on children's physical activity levels. A total of 169 articles were initially identified, of which 11 were eligible for inclusion in the systematic review. Studies were heterogeneous: cross-sectional, RCT, cohort, and direct observation. Study participants were between the ages of 3-15 years, and physical activity was measured by accelerometers, pedometers, direct observation or surveys. A majority of the studies (9/11) found a positive association between time spent outdoors and physical activity in children and adolescents. Of these 9 studies, 5 found this association specifically between time spent outdoors in greenspace and physical activity. Despite limitations, the findings of this review support the positive association between time spent outdoors and physical activity in children and adolescents, and the notion that children and adolescents who spend more time outdoors are more physically active. This demonstrates the need to use outdoor environments as settings for children's and adolescents' physical activity.^

Enhancing Activity Recognition by Fusing Inertial and Biometric Information

Activity recognition is an active research field nowadays, as it enables the development of highly adaptive applications, e.g. in the field of personal health. In this paper, a light high-level fusion algorithm to detect the activity that an individual is performing is presented. The algorithm relies on data gathered from accelerometers placed on different parts of the body, and on biometric sensors. Inertial sensors allow detecting activity by analyzing signal features such as amplitude or peaks. In addition, there is a relationship between the activity intensity and biometric response, which can be considered together with acceleration data to improve the accuracy of activity detection. The proposed algorithm is designed to work with minimum computational cost, being ready to run in a mobile device as part of a context-aware application. In order to enable different user scenarios, the algorithm offers best-effort activity estimation: its quality of estimation depends on the position and number of the available inertial sensors, and also on the presence of biometric information.