Deficits in attentional and executive functioning may interfere with driving ability and result in a lower level of fitness to drive. Studies show mixed results in relation to the consistency of neuropsychological and driving simulator assessment. The objective of this study was to investigate the consistency of both types of assessment. An exploratory correlational analysis was conducted. We found weak, but significant correlations between attention and executive function measures and more efficient driving in the driving simulator. Distractibility was associated with the most evaluated simulator variables. Participants who were better at maintaining attention, eliminating irrelevant information and suppressing inappropriate responses, were less likely to drive above the speed limit, produced a less jerky ride, and used the rearview mirror more regularly.
COBISS.SI-ID: 27996419
In the military, police, security companies, and shooting sports, precision shooting training is of the outmost importance. In order to achieve high shooting accuracy, a lot of training is needed. As a result, trainees use a large number of cartridges and a considerable amount of time of professional trainers, which can cost a lot. Our motivation is to reduce costs and shorten training time by introducing an augmented biofeedback system based on machine learning techniques. We are designing a system that can detect and provide feedback on three types of errors that regularly occur during a precision shooting practice: excessive hand movement error, aiming error and triggering error. The system is designed to provide concurrent feedback on the hand movement error and terminal feedback on the other two errors. Machine learning techniques are used innovatively to identify hand movement errors; the other two errors are identified by the threshold approach. To correct the excessive hand movement error, a precision shot accuracy prediction model based on Random Forest has proven to be the most suitable. The experimental results show that: (1) the proposed Random Forest (RF) model achieves the prediction accuracy of 91.27%, higher than any of the other reference models, and (2) hand movement is strongly related to the accuracy of precision shooting. Appropriate use of the proposed augmented biofeedback system will result in a lower number of rounds used and shorten the precision shooting training process.
COBISS.SI-ID: 25029123
Wearable sensor devices are playing an increasingly important role in providing pervasive and personalized healthcare. Important elements of modern healthcare services are physical rehabilitation and injury prevention. Wearable sensor devices attached to the patient can offer valuable supplemental information to healthcare professionals during treatment or therapy. In physical rehabilitation, wearable inertial sensor devices help therapists to monitor and evaluate parameters and key performance indicators of the rehabilitation activities. Therapy efficiency can be increased by using real-time feedback systems. Three different feedback system architectures are defined and studied: therapist, user, and cloud system. A case study involving rehabilitation therapy based on swimming exercises was performed. Field test results show that the developed sensor device and real-time therapist feedback application provide sufficiently accurate and precise data for the efficient evaluation of swimming parameters. The wide adoption of wearable sensor device based applications will lead to cloud systems where big data analytics will offer additional benefits to healthcare, wellbeing, and quality of life.
COBISS.SI-ID: 12076372
Computationally efficient 3D orientation (3DO) tracking using gyroscope angular velocity measurements enables a short execution time and low energy consumption for the computing device. These are essential requirements in today’s wearable device environments, which are characterized by limited resources and demands for high energy autonomy. We show that the computational efficiency of 3DO tracking is significantly improved by correctly interpreting each triplet of gyroscope measurements as simultaneous (using the rotation vector called the Simultaneous Orthogonal Rotation Angle, or SORA) rather than as sequential (using Euler angles) rotation. For an example rotation of 90°, depending on the change in the rotation axis, using Euler angles requires 35 to 78 times more measurement steps for comparable levels of accuracy, implying a higher sampling frequency and computational complexity. In general, the higher the demanded 3DO accuracy, the higher the computational advantage of using the SORA. Furthermore, we demonstrate that 12 to 14 times faster execution is achieved by adapting the SORA-based 3DO tracking to the architecture of the executing low-power ARM Cortex® M0+ microcontroller using only integer arithmetic, lookup tables, and the small-angle approximation. Finally, we show that the computational efficiency is further improved by choosing the appropriate 3DO computational method. Using rotation matrices is 1.85 times faster than using rotation quaternions when 3DO calculations are performed for each measurement step. On the other hand, using rotation quaternions is 1.75 times faster when only the final 3DO result of several consecutive rotations is needed. We conclude that by adopting the presented practices, the clock frequency of a processor computing the 3DO can be significantly reduced. This substantially prolongs the energy autonomy of the device and enhances its usability in day-to-day measurement scenarios.
COBISS.SI-ID: 14018563
This research paper addresses and discusses different application areas of IoT technology, identifying differences, but also similarities in Smart Cities and Smart Villages ecosystems, while trying to illuminate the standardization efforts that can be applicable in both contexts. Initially, the concept of Smart Cities (urban settlement) originated from the Internet of Things (IoT) technology, however, the use of IoT technology can be extended to the concept of Smart Villages (rural settlement) as well, improving the life of the villagers, and the communities as a whole. Yet, the rural settlements have slightly different requirements than the urban like settlements. If application of IoT in Smart Cities can be characterized by densification of IoT to day-to-day life, following cities’ structural characteristics of being densely settled places, IoT empowered Smart Villages are usually a system of dispersion and deficiency. In the paper we propose the following IoT application domains, which will also serve as a base for research on smart villages: 1. Natural Resources and Energy, 2. Transport and Mobility, 3. Smart Building, 4. Daily Life, 5. Government, and 6. Economy and Society. By providing an overview of technical solutions that support smart solutions in Smart Cities and Smart Villages this research paper evaluates how, with IoT empowered Smart Villages and Smart Cities, an overall improvement of quality of life of their inhabitants can be achieved.
COBISS.SI-ID: 22616067