Evidence map›Paper›PMID 33408668›Full record

ArticleFrontiers in psychology2020

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

Benjamin Strenge, Dirk Koester, Thomas Schack

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Benjamin StrengeNeurocognition and Action Group, Faculty of Psychology and Sports Science, Center for Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.
Dirk KoesterSport Psychology, Faculty Business and Management, BSP Business School Berlin, Berlin, Germany.
Thomas SchackNeurocognition and Action Group, Faculty of Psychology and Sports Science, Center for Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.
Bielefeld University · DEBSP Business & Law School – Hochschule für Management und Recht · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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

Indexed as

cognitive assistance systemsethical issue recognitionkarate athletes/performancekarate katamental representation structuresSDA-M

Identifiers

PMID33408668
PMCPMC7779401
OpenAlexW3114332851

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.