Computational assessment of long-term memory structures from SDA-M related to action sequences

Cognitive representation of gait: differences in memory structures between individuals after total knee arthroplasty and total hip arthroplasty

The objective was to examine differences in the gait-specific cognitive representation structures between individuals after total knee- (TKA) and after total hip-joint arthroplasty (THA). The cognitive representation structure was compared between three groups: 1. three months after TKA (n = 12), 2. three months after THA (n = 12), and 3. healthy control group (CG) (n = 12) using the structural dimensional analysis of mental representation (SDA-M). Additionally, perceived joint function was rated by either the KOOS, JR. or HOOS, JR. Mean distribution of perceived joint function was not significantly different between the TKA (60.35 ± 11.2) and THA group (68.01 ± 13.8) (t = - 1.425; p = .173). In the cognitive representation structure, the THA group exhibited functional differences from the TKA group and control group, both of which showed a functional structure. Three months after hip joint replacement the gait-specific cognitive representation structure seems to reflect joint function-specific deviations. Therefore, focussing on functional recovery of cognitive gait representation may facilitate gait rehabilitation in individuals after hip replacement.

Expertise-dependent differences in mental representation metrics of pas de bourrée

Precise movement control is of prime importance in almost every kind of sport and greatly influences an athlete's performance. In dancing not only motor but also cognitive skills, e.g. in the form of memorized representational structures, are essential components of the performance. This study investigated different metrics related to the long-term memory of ballet dancers with different skill levels regarding the pas de bourrée using the structural-dimensional analysis of mental representations (SDA-M) method. To this end, the Correct Action Selection Probability Analysis (CASPA) algorithm, a recent SDA-M extension that predicts the individual probabilities of correct action selections within a movement sequence, has been applied in the context of dancing for the first time. Significant positive correlations were found between participants' degree of expertise and the proximity of their mental representation structure to the ideal reference structure, as well as between the degree of expertise and the probability of correct action selection within the movement sequence estimated by CASPA. The results indicate that increased training experience in ballet dancing is not only associated with functionally better structured mental representations of the movement sequence but also with a higher probability of correct action selection. These findings provide further evidence for SDA-M with CASPA as an auspicious tool for individualized task-related memory assessments and diagnostics in different action sequences, e.g. as the basis for mental training.

Cognitive assistance for action selection: Challenges and approaches

Cognitive assistance systems aim at compensating shortcomings of natural cognition concerning specific activities. Notable progress has been made regarding data acquisition, analysis, and the exploration of technical means for supporting human action selection and execution. The related challenges and potential solutions can be associated to four largely independent questions: What actions should be executed, when this must or should be done, whether assistance is needed for a specific action, and if so, how the action should be supported. A broad range of technological and methodical approaches can be taken for tackling each of these issues, including recent advances and new challenges in the automatized analysis of task-related mental representation structures.

Empirical relationships between algorithmic SDA-M-based memory assessments and human errors in manual assembly tasks

The majority of manufacturing tasks are still performed by human workers, and this will probably continue to be the case in many industry 4.0 settings that aim at highly customized products and small lot sizes. Technical systems could assist on-the-job training and execution of these manual assembly processes, using augmented reality and other means, by properly treating and supporting workers' cognitive resources. Recent algorithmic advancements automatized the assessment of task-related mental representation structures based on SDA-M, which enables technical systems to anticipate mistakes and provide corresponding user-specific assistance. Two studies have empirically investigated the relations between algorithmic assessments of individual memory structures and the occurrences of human errors in different assembly tasks. Hereby theoretical assumptions of the automatized SDA-M assessment approaches were deliberately violated in realistic ways to evaluate the practical applicability of these approaches. Substantial but imperfect correspondences were found between task-related mental representation structures and actual performances with sensitivity and specificity values ranging from 0.63 to 0.72, accompanied by prediction accuracies that were highly significant above chance level.

Facilitating Workers’ Task Proficiency with Subtle Decay of Contextual AR-Based Assistance Derived from Unconscious Memory Structures

Contemporary assistance systems support a broad variety of tasks. When they provide information or instruction, the way they do it has an implicit and often not directly graspable impact on the user. System design often forces static roles onto the user, which can have negative side effects when system errors occur or unique and previously unknown situations need to be tackled. We propose an adjustable augmented reality-based assistance infrastructure that adapts to the user’s individual cognitive task proficiency and dynamically reduces its active intervention in a subtle, not consciously noticeable way over time to spare attentional resources and facilitate independent task execution. We also introduce multi-modal mechanisms to provide context-sensitive assistance and argue why system architectures that provide explainability of concealed automated processes can improve user trust and acceptance.

Cognitive Interaction Technology in Sport-Improving Performance by Individualized Diagnostics and Error Prediction

The interdisciplinary research area Cognitive Interaction Technology (CIT) aims to understand and support interactions between human users and other elements of socio-technical systems. Important reasons for the new interest in understanding CIT in sport psychology are the impressive development of cognitive robotics and advanced technologies such as virtual or augmented reality systems, cognitive glasses or neurotechnology settings. The present article outlines this area of research, addresses ethical issues, and presents an empirical study in the context of a new measurement and assessment system for training in karate. Recent advances in the field of cognitive assistance systems enabled largely automatized assessments of individual mental representation structures for action sequences, such as choreographed movement patterns in dance or martial arts. Empirical investigations with karate practitioners of different skill levels demonstrate that advanced software-based survey and algorithmic analysis procedures based on cognitive models generate individualized performance predictions for a movement sequence from the Kanku-dai kata (a pre-defined karate movement sequence), which correlated significantly not only with formal expertise (kyu/dan rank) but also with the actual likelihood of mistakes in action execution. This information could prospectively be used to define individual training goals for deliberate practice and incorporated into cognitive interaction technology to provide appropriate feedback. We argue that the development of cognitive interaction systems for sport should explicitly take ethical issues into consideration and present a particular developed engineering approach. The potential benefits of such an assistance system for intermediate and advanced practitioners include more effective and flexible practice, as well as supportive effects, and more flexible training schedules. Furthermore, we argue that researchers from the field of sport psychology can benefit from advances in technological systems that enhance the understanding of mental and motor control in skilled voluntary action.