This study investigates the engagement of young people in foreign language learning. Specifically, engagement is defined as a metaconstruct consisting of the following components: cognitive, emotional, and social. An attempt was made to quantify these individual engagement components within task-based and communicative-oriented lessons. We employed electrocardiographic and accelerometric measurements to monitor learners’ physiological responses to engagement during regular German classes. The second part of the project was a questionnaire-based study measuring the subjective opinions of learners about their engagement. The results of the research support the adoption of a task-based approach. We observed the highest level of engagement during productive tasks, which can serve as a rationale for teachers to increase the number of productive tasks compared to receptive ones. Moreover, including the peer-learning component in the activities appeared to be of considerable importance due to its role in building intrinsic motivation to learn and in stimulating the growth of social competences.

Mechanomyography (MMG) is a technique of recording muscles activity that may be considered a suitable choice for human–machine interfaces (HMI). The design of sensors used for MMG and their spatial distribution are among the deciding factors behind their successful implementation to HMI. We present a new design of a MMG sensor, which consists of two coupled piezoelectric discs in a single housing. The sensor’s functionality was verified in two experimental setups related to typical MMG applications: an estimation of the force/MMG relationship under static conditions and a neural network-based gesture classification. The results showed exponential relationships between acquired MMG and exerted force (for up to 60% of the maximal voluntary contraction) alongside good classification accuracy (94.3%) of eight hand motions based on MMG from a single-site acquisition at the forearm. The simplification of the MMG-based HMI interface in terms of spatial arrangement is rendered possible with the designed sensor.

Parkinson’s disease results in motor impairment that deteriorates patients’ quality of life. One of the symptoms negatively interfering with daily activities is kinetic tremor which should be measured to monitor the outcome of therapy. A new instrumented method of quantification of the kinetic tremor is proposed, based on the analysis of circles drawn on a digitizing tablet by a patient. The aim of this approach is to obtain a tremor scoring equivalent to that performed by trained clinicians. Models are trained with the least absolute shrinkage and selection operator (LASSO) method to predict the tremor scores on the basis of the parameters computed from the patients’ drawings. Signal parametrization is derived from both expert knowledge and the response of an artificial neural network to the raw data, thus the approach was named multimodal. The fitted models are eventually combined into model ensembles that provide aggregated scores of the kinetic tremor captured in the drawings. The method was verified with a set of clinical data acquired from 64 Parkinson’s disease patients. Automated and objective quantification of the kinetic tremor with the presented approach yielded promising results, as the Pearson’s correlations between the visual ratings of tremor and the model predictions ranged from 0.839 to 0.890 in the best-performing models.

Operation of an articulated vehicle is dependent on an appropriate damping action taking place in its rotary articulation. In order to analyse an impact of the control of the articulation on the motion of the vehicle a model of the vehicle with a controllable hydraulic damping system has been developed. A 90 degree turn and lane change manoeuvres were simulated using LabVIEW software. Modification of the damping parameters of the articulation, according to the velocity and articulation angle of the vehicle, proved to have a significant impact on the vehicle motion stability. Moreover, the sensor layer necessary for the control algorithm as well as the diagnostic system is described.