Evidence map›Paper›PMID 38257621›Full record

ArticleSensors (Basel, Switzerland)2024

Integrated Quantitative Evaluation of Spatial Cognition and Motor Function with HoloLens Mixed Reality.

Kenya Tada, Yuhei Sorimachi, Kyo Kutsuzawa, Dai Owaki, Mitsuhiro Hayashibe

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

5 citing papers in PubMed, 12 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

5 authors at 1 institution in 1 country.

Kenya TadaNeuro-Robotics Lab, Department of Robotics, Graduate School of Engineering and also with Graduate School of Biomedical Engineering, Tohoku University, Sendai 980-8579, Japan.
Yuhei SorimachiNeuro-Robotics Lab, Department of Robotics, Graduate School of Engineering and also with Graduate School of Biomedical Engineering, Tohoku University, Sendai 980-8579, Japan.
Kyo KutsuzawaNeuro-Robotics Lab, Department of Robotics, Graduate School of Engineering and also with Graduate School of Biomedical Engineering, Tohoku University, Sendai 980-8579, Japan.ORCID 0000-0002-5326-7847
Dai OwakiNeuro-Robotics Lab, Department of Robotics, Graduate School of Engineering and also with Graduate School of Biomedical Engineering, Tohoku University, Sendai 980-8579, Japan.ORCID 0000-0003-1217-3892
Mitsuhiro HayashibeNeuro-Robotics Lab, Department of Robotics, Graduate School of Engineering and also with Graduate School of Biomedical Engineering, Tohoku University, Sendai 980-8579, Japan.ORCID 0000-0001-6179-5706
Tohoku University · JP

Funding

Japan Society for the Promotion of Science 22H04764
6 · The paper itself

Abstract

The steady increase in the aging population worldwide is expected to cause a shortage of doctors and therapists for older people. This demographic shift requires more efficient and automated systems for rehabilitation and physical ability evaluations. Rehabilitation using mixed reality (MR) technology has attracted much attention in recent years. MR displays virtual objects on a head-mounted see-through display that overlies the user's field of vision and allows users to manipulate them as if they exist in reality. However, tasks in previous studies applying MR to rehabilitation have been limited to tasks in which the virtual objects are static and do not interact dynamically with the surrounding environment. Therefore, in this study, we developed an application to evaluate cognitive and motor functions with the aim of realizing a rehabilitation system that is dynamic and has interaction with the surrounding environment using MR technology. The developed application enabled effective evaluation of the user's spatial cognitive ability, task skillfulness, motor function, and decision-making ability. The results indicate the usefulness and feasibility of MR technology to quantify motor function and spatial cognition both for static and dynamic tasks in rehabilitation.

Indexed as

Augmented RealityPhysiciansSpatial NavigationAgedAgingCognitionHumanscognitive abilitygame-based rehabilitationHoloLens2mixed realitymotor function

Identifiers

PMID38257621
PMCPMC10819263
OpenAlexW4390878459

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.