Investigation of Acoustic Influencing Parameters to Increase the Human Performance Potential in Simultaneous Driving and Working Operation of Armoured Vehicles

Humanitarian and physiological restrictions prevent the optimal execution and use of the corresponding technical achievement in various situations. For example, working simultaneously while driving in vehicle under vibration, noise, confinement and heat often leads to dizziness, nausea and finally even vomiting-all symptoms which significantly limit human performance. This phenomenon is one of the oldest protective reaction of the human organism and has been deeply investigated e.g. under the name simulator sickness or motion sickness. Unfortunately, new mobility concepts as autonomous driving vehicle always include the vision of parallel working activities while driving. For working crew members in military land vehicles, the situation is even worse due to the restricted outside view and body motion of protected all-terrain vehicle. In earlier projects the dependency of mechanical vibration and motion sickness was investigated. This paper now explains the determination of acoustic properties and threshold values for vehicle that enable ergonomic working at mobile workplaces without negatively influencing the human performance. The purpose of this first phase of the project was to create and validate an experimental setup, in which a sound exposure of test person with frequencies up to the infrasound range could be realized with help of an appropriate acoustic equipment. Psychological tests have been performed in parallel, so the cognitive performance of the test person was evaluated during exposition with sound. Based on field tests statistically found threshold values for a maximum exposure with low-frequency noise in vehicles with parallel working activities will be derived.

On-farm testing of dairy calves' avoidance response to human approach: Effects of sex, age and test order

Human approach tests are generally accepted as valid measures of the human-animal relationship and hence are widely included in on-farm welfare assessment protocols. Most measures of avoidance response to human approach in production animals have been developed and tested under experimental conditions rather than on commercial farms, thereby making the results less relevant for operational on-farm animal welfare assessment. By contrast, the current study was conducted on calves in their home pens. On 110Norwegian dairy farms, 548 group-housed calves (aged 22 288 days) were tested individually for their behavioural response to an unfamiliar human approach by a single test person. To conduct the test, the respective calf manager administered concentrates to the manger, followed by the test person who approached each animal in turn in a standardised manner. The avoidance response of the individual calf was categorised as 0 to 5 (maximal to no avoidance) in reaction to an attempted approach and head touch by the test person. The statistical analyses showed that heifer calves were more avoidant compared to bull calves, as were younger bulls compared to older bulls, and that overall avoidance increased in calves that were not tested first.

Feature Selection for Machine Learning Based Step Length Estimation Algorithms

An accurate step length estimation can provide valuable information to different applications such as indoor positioning systems or it can be helpful when analyzing the gait of a user, which can then be used to detect various gait impairments that lead to a reduced step length (caused by e.g., Parkinson’s disease or multiple sclerosis). In this paper, we focus on the estimation of the step length using machine learning techniques that could be used in an indoor positioning system. Previous step length algorithms tried to model the length of a step based on measurements from the accelerometer and some tuneable (user-specific) parameters. Machine-learning-based step length estimation algorithms eliminate these parameters to be tuned. Instead, to adapt these algorithms to different users, it suffices to provide examples of the length of multiple steps for different persons to the machine learning algorithm, so that in the training phase the algorithm can learn to predict the step length for different users. Until now, these machine learning algorithms were trained with features that were chosen intuitively. In this paper, we consider a systematic feature selection algorithm to be able to determine the features from a large collection of features, resulting in the best performance. This resulted in a step length estimator with a mean absolute error of 3.48 cm for a known test person and 4.19 cm for an unknown test person, while current state-of-the-art machine-learning-based step length estimators resulted in a mean absolute error of 4.94 cm and 6.27 cm for respectively a known and unknown test person.

Effect of rowing posture on body measurements and skin–sportswear interface pressure and implications on garment fit

Sportswear should fit well each individual athlete while preserving its ergonomic and pressure comfort upon sport-specific movements. This study aims to quantify the effect of two rowing postures on selected body measurements and skin–sportswear interface pressure for competitive rowers of age 18–35. The results based on average body measurements of a total number of 74 male and female rowers indicate a considerable influence of the catch and finish posture on both body measurements and interface skin–sportswear pressure, regardless of the gender. Back length and across back width were the most affected by posture, and increased especially from the static to catch position by 12% (6.1 cm) and 16% (6.5 cm) for male rowers, and respectively by 11% (4.9 cm) and 13% (4.7 cm) for female rowers. In general, the posture led to the larger influence on pressure than on anthropometrics of maximum 55% versus 16% for male and up to 82% versus 13% for female rowers, respectively. The maximum interface pressure (e.g. 10 mmHg) was rather low, which suggest there was no pressure discomfort. Prototypes were developed and the fit of garments was investigated in various postures. For the considered fabrics and design, an increase of the garment pattern to accommodate the catch maximum changes led to a poor fit of the prototype MR58-CP, which was generally too large, especially in the static posture. On the contrary, prototype MR58-FP that considered some finish rowing posture-related body changes and design adjustments based on experience with the first prototype and input from the test person had the best fit.

3D-based visual physical activity assessment of children

In the last decades, an alarming rise in prevalence of childhood overweight and obesity has been observed which is partly attributed to a lack in physical activity and has started to become a public health concern. Therefore, the necessity for accurate physical activity assessment has become more and more apparent. Physical activity can be assessed objectively using accelerometers or combined devices. The application of such devices is sometimes complex and wearing the device may influence the behaviour of the test person. Therefore, assessment without any worn device would be an advantage.A RGB-D camera device captures motion of the test person in a specific measurement area. After reducing the data and subtraction of the voxel distance, an activity level can be calculated.The calculated activity level is similar to acceleration data of common monitoring devices. The calculated activity level is the sum of the person’s activity. Little activity with small movement can be differentiated from intense activity with large movement and high acceleration as well as no activity. The data can be structured in body-activity and limb-activity. Classifying those categories increases the benefit of this assessment compared to common accelerometers.With the RGB-D based assessment objective, contextual information of different physical activity levels can be provided. Physical activity assessment without a worn device offers advantages such as the lack of manipulation of the device and its positioning, also the person’s compliance is no issue influencing the assessment. The RGB-D based assessment is similar to acceleration data and can be converted into comparable data and units after calibration. For more specific assessments a validation with accelerometers and the calibration of the derived data is necessary.

Application of Simulators and Simulation Tools for the Functional Design of Mechatronic Systems

This paper considers the application of simulators or demonstrators in the development of mechatronic products. It is shown at what step of the mechatronic design process a simulator or demonstrator can be used to significantly improve a products quality and thus identify possible errors and provide potential workarounds. Cost reduction is achieved by the use of simulators or demonstrators in the early design stage and less real product tests have to be carried out which also could be hazardous for the test person.