TY - GEN
T1 - Assessment of a Novel Virtual Environment for Examining Human Cognitive-Motor Performance During Execution of Action Sequences
AU - Shaver, Alexandra A.
AU - Peri, Neehar
AU - Mezebish, Remy
AU - Matthew, George
AU - Berson, Alyza
AU - Gaskins, Christopher
AU - Davis, Gregory P.
AU - Katz, Garrett E.
AU - Samuel, Immanuel
AU - Reinhard, Matthew J.
AU - Costanzo, Michelle E.
AU - Reggia, James A.
AU - Purtilo, James
AU - Gentili, Rodolphe J.
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - The examination of neural resource allocation during complex action sequence execution is critical to understanding human behavior. While physical systems are usually used for such assessment, virtual/remote systems offer other approaches with potential benefits such as remote training/evaluation. Here we describe a virtual environment (VLEARN) operated via the internet that has been developed to study the cognitive-motor mechanisms underlying the execution of goal-oriented action sequences in remote and laboratory settings. This study aimed to i) examine the feasibility of evaluating human cognitive-motor behavior when individuals operate VLEARN to complete various tasks; and ii) assess VLEARN by comparing its usability and the resulting performance, mental workload, and mental/physical fatigue during virtual and physical task execution. Results revealed that our approach allowed human cognitive-motor behavior assessment as the tasks completed physically and virtually via VLEARN had similar success rates. Also, there was a relationship between the complexity of the virtual control systems and the dependency on those to complete tasks. Namely, relative to controls with more functionalities, when VLEARN enabled simpler controls, above average usability and similar levels of cognitive-motor performance for both physical and virtual task execution were observed. Thus, a simplification of some aspects of the VLEARN control interface should enhance its usability. Our approach is promising for examining human cognitive-motor behavior and informing multiple applications (e.g., telehealth, remote training).
AB - The examination of neural resource allocation during complex action sequence execution is critical to understanding human behavior. While physical systems are usually used for such assessment, virtual/remote systems offer other approaches with potential benefits such as remote training/evaluation. Here we describe a virtual environment (VLEARN) operated via the internet that has been developed to study the cognitive-motor mechanisms underlying the execution of goal-oriented action sequences in remote and laboratory settings. This study aimed to i) examine the feasibility of evaluating human cognitive-motor behavior when individuals operate VLEARN to complete various tasks; and ii) assess VLEARN by comparing its usability and the resulting performance, mental workload, and mental/physical fatigue during virtual and physical task execution. Results revealed that our approach allowed human cognitive-motor behavior assessment as the tasks completed physically and virtually via VLEARN had similar success rates. Also, there was a relationship between the complexity of the virtual control systems and the dependency on those to complete tasks. Namely, relative to controls with more functionalities, when VLEARN enabled simpler controls, above average usability and similar levels of cognitive-motor performance for both physical and virtual task execution were observed. Thus, a simplification of some aspects of the VLEARN control interface should enhance its usability. Our approach is promising for examining human cognitive-motor behavior and informing multiple applications (e.g., telehealth, remote training).
KW - Action sequences
KW - Cognitive-motor performance
KW - Human-machine interface
KW - Mental workload
KW - Rehabilitation
KW - Virtual environment
UR - http://www.scopus.com/inward/record.url?scp=85133293029&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85133293029&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-05457-0_28
DO - 10.1007/978-3-031-05457-0_28
M3 - Conference contribution
AN - SCOPUS:85133293029
SN - 9783031054563
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 361
EP - 380
BT - Augmented Cognition - 16th International Conference, AC 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Proceedings
A2 - Schmorrow, Dylan D.
A2 - Fidopiastis, Cali M.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 16th International Conference on Augmented Cognition, AC 2022 Held as Part of the 24th HCI International Conference, HCII 2022
Y2 - 26 June 2022 through 1 July 2022
ER -