TY - GEN
T1 - Designing medical interactive systems via assessment of human mental workload
AU - Longo, Luca
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6
Y1 - 2015/6
N2 - In clinical settings, Human-computer systems need to be designed in a way that medical errors are reduced and patient care is enhanced. Inspection methods are usually employed in HCI to assess usability of interactive systems. However, they do not consider the state of the operator while executing a task, the surrounding environment and the task demands. It is argued that assessing performance of operators is fundamental for designing optimal systems with which healthcare can be effectively delivered. The aim of our solution is to assess performance of operators employing the notion of Mental Workload (MWL) this being a construct believed to strongly correlate with performance. The proposal is to develop a model for MWL assessment using supervised machine learning. This model will be evaluated via user studies involving clinicians and operators interacting with a set of medical systems. Assessments of MWL will be compared and validated with objective indexes of performance such as error rate and task execution time.
AB - In clinical settings, Human-computer systems need to be designed in a way that medical errors are reduced and patient care is enhanced. Inspection methods are usually employed in HCI to assess usability of interactive systems. However, they do not consider the state of the operator while executing a task, the surrounding environment and the task demands. It is argued that assessing performance of operators is fundamental for designing optimal systems with which healthcare can be effectively delivered. The aim of our solution is to assess performance of operators employing the notion of Mental Workload (MWL) this being a construct believed to strongly correlate with performance. The proposal is to develop a model for MWL assessment using supervised machine learning. This model will be evaluated via user studies involving clinicians and operators interacting with a set of medical systems. Assessments of MWL will be compared and validated with objective indexes of performance such as error rate and task execution time.
KW - Human Mental Workload
KW - Human-Computer Interaction
KW - Interactive Systems
KW - Machine Learning
KW - Medical applications
UR - http://www.scopus.com/inward/record.url?scp=84944266295&partnerID=8YFLogxK
U2 - 10.1109/CBMS.2015.67
DO - 10.1109/CBMS.2015.67
M3 - Conference contribution
AN - SCOPUS:84944266295
T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems
SP - 364
EP - 365
BT - Proceedings - IEEE 28th International Symposium on Computer-Based Medical Systems, CBMS 2015
A2 - Traina, Caetano
A2 - Pereira Rodrigues, Pedro
A2 - Kane, Bridget
A2 - de Azevedo-Marques, Paulo Mazzoncini
A2 - Machado Traina, Agma Juci
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2015
Y2 - 22 June 2015 through 25 June 2015
ER -
