Changes In Cognitive Workload Research Articles

Developing cognitive workload and performance evaluation models using functional brain network analysis

Cognition, defined as the ability to learn, remember, sustain attention, make decisions, and solve problems, is essential in daily activities and in learning new skills. The purpose of this study was to develop cognitive workload and performance evaluation models using features that were extracted from Electroencephalogram (EEG) data through functional brain network and spectral analyses. The EEG data were recorded from 124 brain areas of 26 healthy participants conducting two cognitive tasks on a robot simulator. The functional brain network and Power Spectral Density features were extracted from EEG data using coherence and spectral analyses, respectively. Participants reported their perceived cognitive workload using the SURG-TLX questionnaire after each exercise, and the simulator generated actual performance scores. The extracted features, actual performance scores, and subjectively assessed cognitive workload values were used to develop linear models for evaluating performance and cognitive workload. Furthermore, the Pearson correlation was used to find the correlation between participants’ age, performance, and cognitive workload. The findings demonstrated that combined EEG features retrieved from spectral analysis and functional brain networks can be used to evaluate cognitive workload and performance. The cognitive workload in conducting only Matchboard level 3, which is more challenging than Matchboard level 2, was correlated with age (0.54, p-value = 0.01). This finding may suggest playing more challenging computer games are more helpful in identifying changes in cognitive workload caused by aging. The findings could open the door for a new era of objective evaluation and monitoring of cognitive workload and performance.

Assessment of learning in simulator-based arthroscopy training with the diagnostic arthroscopy skill score (DASS) and neurophysiological measures.

Virtual arthroscopic training has become increasingly popular. However, there is a lack of efficiency-based tracking of the trainee, which may be critical for determining the specifics of training programs and adapting them for the needs of each trainee. This study aims to evaluate and compare the measures obtained with a non-invasive neurophysiological method with The Diagnostic Arthroscopy Skill Score (DASS), a commonly used assessment tool for evaluating arthroscopic skills. The study collected simulator performance scores, consisting of "Triangulation Right Hand", "Triangulation Left Hand", "Catch the Stars" and "Three Rings" and DASS scores from 22 participants (11 novices, 11 experts). These scores were obtained while participants underwent a structured program of exercises for the fundamentals of arthroscopic surgery training (FAST) and knee module using a simulator-based arthroscopy device. During the evaluation, data on oxy-hemoglobin and deoxy-hemoglobin levels in the prefrontal cortex were collected using the Functional Near-Infrared Spectroscopy (fNIRS) imaging system. Performance scores, DASS scores, and fNIRS data were subsequently analyzed to determine any correlation between performance and cortex activity. The simulator performance scores and the DASSPart2 scores were significantly higher in the expert group compared to the novice group (200.1 ± 28.5 vs 172.5 ± 48.9, p = 0.04 and 9.4 ± 5.6 vs. 5.4 ± 5.6 p = 0.02). In the expert group, fNIRS data showed a significantly lower prefrontal cortex activation during fundamental tasks in the FAST module, indicating significantly more efficient mental resource use. The analysis of cognitive workload changes during simulation-based arthroscopy training revealed a significant correlation between the trainees' DASS scores and fNIRS data. This correlation suggests the potential use of fNIRS data and DASS scores as additional metrics to create adaptive training protocols for each participant. By incorporating these metrics, the training process can be optimized, leading to more efficient arthroscopic training and better preparedness for clinical operations. III.

Cognitive Workload of Novice Forklift Truck Drivers in VR-based Training

There is increasing use of Virtual Reality (VR) to train forklift truck operators but a lack of sufficient understanding of how cognitive workload changes with respect to different task demands in VR-based training. In this study, 19 novice participants completed three forklift driving lessons with varying difficulty levels (low, medium, and high) using a VR simulator. To examine the effect of repeated training on cognitive workload, two sessions were repeated by participants using the same procedures. Cognitive workload was assessed with objective (electroencephalogram [EEG] activity) and subjective (NASA-TLX) measurements. EEG theta power and NASA-TLX (mental workload) scores were significantly higher for high than low difficulty levels. However, both EEG and NASA-TLX responses were reduced with repeated training in the second session. These findings highlight the effectiveness of EEG in continuous monitoring of workload variation caused by task difficulty and implementing training programs to moderate cognitive workload for forklift operators.

Using electroencephalography to analyse drivers' different cognitive workload characteristics based on on-road experiment.

Driver's cognitive workload has an important impact on driving safety. This paper carries out an on-road experiment to analyse the impact from three innovative aspects: significance analysis of electroencephalogram (EEG) under different cognitive workloads, distribution of EEG maps with different frequency signals and influence of different cognitive workloads on driving safety based on EEG. First, the EEG signals are processed and four frequencies of delta, theta, alpha and beta are obtained. Then, the time-frequency transform and power spectral density calculation are carried out by short-time Fourier to study the correlation of each frequency signal of different workload states, as well as the distribution pattern of the EEG topographic map. Finally, the time and space energy and phase changes in each cognitive task event are studied through event-related spectral perturbation and inter-trial coherence. Results show the difference between left and right brains, as well as the resource occupancy trends of the monitor, perception, visual and auditory channels in different driving conditions. Results also demonstrate that the increase in cognitive workloads will directly affect driving safety. Changes in cognitive workload have different effects on brain signals, and this paper can provide a theoretical basis for improving driving safety under different cognitive workloads. Mastering the EEG characteristics of signals can provide more targeted supervision and safety warnings for the driver.

Reliability of MUSE 2 and Tobii Pro Nano at capturing mobile application users' real-time cognitive workload changes.

Despite the importance of cognitive workload in examining the usability of smartphone applications and the popularity of smartphone usage globally, cognitive workload as one attribute of usability tends to be overlooked in Human-Computer Interaction (HCI) studies. Moreover, limited studies that have examined the cognitive workload aspect often measured some summative workloads using subjective measures (e.g., questionnaires). A significant limitation of subjective measures is that they can only assess the overall, subject-perceived cognitive workload after the procedures/tasks have been completed. Such measurements do not reflect the real-time workload fluctuation during the procedures. The reliability of some devices on a smartphone setting has not been thoroughly evaluated. This study used mixed methods to empirically study the reliability of an eye-tracking device (i.e., Tobii Pro Nano) and a low-cost electroencephalogram (EEG) device (i.e., MUSE 2) for detecting real-time cognitive workload changes during N-back tasks. Results suggest that the EEG measurements collected by MUSE 2 are not very useful as indicators of cognitive workload changes in our setting, eye movement measurements collected by Tobii Pro Nano with mobile testing accessory are useful for monitoring cognitive workload fluctuations and tracking down interface design issues in a smartphone setting, and more specifically, the maximum pupil diameter is the preeminent indicator of cognitive workload surges. In conclusion, the pupil diameter measure combined with other subjective ratings would provide a comprehensive user experience assessment of mobile applications. They can also be used to verify the successfulness of a user interface design solution in improving user experience.

Analysis of Dynamic Changes in Cognitive Workload During Cardiac Surgery Perfusionists' Interactions With the Cardiopulmonary Bypass Pump.

This novel preliminary study sought to capture dynamic changes in heart rate variability (HRV) as a proxy for cognitive workload among perfusionists while operating the cardiopulmonary bypass (CPB) pump during real-life cardiac surgery. Estimations of operators' cognitive workload states in naturalistic settings have been derived using noninvasive psychophysiological measures. Effective CPB pump operation by perfusionists is critical in maintaining the patient's homeostasis during open-heart surgery. Investigation into dynamic cognitive workload fluctuations, and their relationship with performance, is lacking in the literature. HRV and self-reported cognitive workload were collected from three Board-certified cardiac perfusionists (N = 23 cases). Five HRV components were analyzed in consecutive nonoverlapping 1-min windows from skin incision through sternal closure. Cases were annotated according to predetermined phases: prebypass, three phases during bypass, and postbypass. Values from all 1min time windows within each phase were averaged. Cognitive workload was at its highest during the time between initiating bypass and clamping the aorta (preclamp phase during bypass), and decreased over the course of the bypass period. We identified dynamic, temporal fluctuations in HRV among perfusionists during cardiac surgery corresponding to subjective reports of cognitive workload. Not only does cognitive workload differ for perfusionists during bypass compared with pre- and postbypass phases, but differences in HRV were also detected within the three bypass phases. These preliminary findings suggest the preclamp phase of CPB pump interaction corresponds to higher cognitive workload, which may point to an area warranting further exploration using passive measurement.

Measuring the Cognitive Workload During Dual-Task Walking in Young Adults: A Combination of Neurophysiological and Subjective Measures.

Background: Walking while performing a secondary task (dual-task (DT) walking) increases cognitive workload in young adults. To date, few studies have used neurophysiological measures in combination to subjective measures to assess cognitive workload during a walking task. This combined approach can provide more insights into the amount of cognitive resources in relation with the perceived mental effort involving in a walking task.Research Question: The objective was to examine cognitive workload in young adults during walking conditions varying in complexity.Methods: Twenty-five young adults (mean = 24.4 ± 5.4) performed four conditions: (1) usual walking, (2) simple DT walking, (3) complex DT walking and (4) standing while subtracting. During the walking task, mean speed, cadence, stride time, stride length, and their respective coefficient of variation (CV) were recorded. Cognitive workload will be measured through changes in oxy- and deoxy-hemoglobin (ΔHbO2 and ΔHbR) during walking in the dorsolateral prefrontal cortex (DLPFC) and perceived mental demand score from NASA-TLX questionnaire.Results: In young adults, ΔHbO2 in the DLPFC increased from usual walking to both DT walking conditions and standing while subtracting condition. ΔHbO2 did not differ between the simple and complex DT and between the complex DT and standing while subtracting condition. Perceived mental demand gradually increased with walking task complexity. As expected, all mean values of gait parameters were altered according to task complexity. CV of speed, cadence and stride time were significantly higher during DT walking conditions than during usual walking whereas CV of stride length was only higher during complex DT walking than during usual walking.Significance: Young adults had greater cognitive workload in the two DT walking conditions compared to usual walking. However, only the mental demand score from NASA-TLX questionnaire discriminated simple from complex DT walking. Subjective measure provides complementary information to objective one on changes in cognitive workload during challenging walking tasks in young adults. These results may be useful to improve our understanding of cognitive workload during walking.

The Effects of Increased Visual Information on Cognitive Workload in a Helicopter Simulator.

To test the effects of enhanced display information ("symbology") on cognitive workload in a simulated helicopter environment, using the detection response task (DRT). Workload in highly demanding environments can be influenced by the amount of information given to the operator and consequently it is important to limit potential overload. Participants (highly trained military pilots) completed simulated helicopter flights, which varied in visual conditions and the amount of information given. During these flights, participants also completed a DRT as a measure of cognitive workload. With more visual information available, pilots' landing accuracy was improved across environmental conditions. The DRT is sensitive to changes in cognitive workload, with workload differences shown between environmental conditions. Increasing symbology appeared to have a minor effect on workload, with an interaction effect of symbology and environmental condition showing that symbology appeared to moderate workload. The DRT is a useful workload measure in simulated helicopter settings. The level of symbology-moderated pilot workload. The increased level of symbology appeared to assist pilots' flight behavior and landing ability. Results indicate that increased symbology has benefits in more difficult scenarios. The DRT is an easily implemented and effective measure of cognitive workload in a variety of settings. In the current experiment, the DRT captures the increased workload induced by varying the environmental conditions, and provides evidence for the use of increased symbology to assist pilots.

Tactile detection response task: Metrics for assessing drivers’ cognitive workload

The Tactile Detection Response Task (TDRT) has been used to assess the cognitive workload of driver distraction with response time and miss rate as metrics of cognitive workload. However, it is not clear which metric is more sensitive and whether sensitivity is maintained for visual tasks. The objective of this study was to assess the sensitivity of the TDRT to changes in cognitive workload and to examine whether the sensitivity depends on task modality. A driving simulator study was conducted with 24 participants. The study included restaurant selection tasks with three presentation modalities (auditory, visual, and hybrid) and two difficulty levels (low and high). The high difficulty level was designed to be more cognitively demanding than the low difficulty level. Mixed-effects models were applied to examine the TDRT metrics and task difficulty level. The model controlled for age group, gender, and included a random effect for participants. The high difficulty level of the auditory tasks significantly increased the likelihood of missing a TDRT stimulus. No statistically significant differences were observed for visual and hybrid tasks. TDRT response time was not significantly associated with the difficulty level, regardless of task modality. In this study, the binary outcome TDRT miss was thus considered a more sensitive metric of cognitive workload than TDRT response time. TDRT response time can still be used to measure cognitive workload when tasks are relatively easy and the TDRT miss rate is close to zero. In addition, the sensitivity of the TDRT miss diminished for tasks that involved a visual component. Researchers who use TDRT to measure the cognitive workload associated with visual tasks should be aware of this limitation.

The effects of cognitive distraction on behavioural, oculomotor and electrophysiological metrics during a driving hazard perception task

Previous research has demonstrated that the distraction caused by holding a mobile telephone conversation is not limited to the period of the actual conversation (Haigney, 1995; Redelmeier & Tibshirani, 1997; Savage et al., 2013). In a prior study we identified potential eye movement and EEG markers of cognitive distraction during driving hazard perception. However the extent to which these markers are affected by the demands of the hazard perception task are unclear. Therefore in the current study we assessed the effects of secondary cognitive task demand on eye movement and EEG metrics separately for periods prior to, during and after the hazard was visible. We found that when no hazard was present (prior and post hazard windows), distraction resulted in changes to various elements of saccadic eye movements. However, when the target was present, distraction did not affect eye movements.We have previously found evidence that distraction resulted in an overall decrease in theta band output at occipital sites of the brain. This was interpreted as evidence that distraction results in a reduction in visual processing. The current study confirmed this by examining the effects of distraction on the lambda response component of subjects eye fixation related potentials (EFRPs). Furthermore, we demonstrated that although detections of hazards were not affected by distraction, both eye movement and EEG metrics prior to the onset of the hazard were sensitive to changes in cognitive workload. This suggests that changes to specific aspects of the saccadic eye movement system could act as unobtrusive markers of distraction even prior to a breakdown in driving performance.

Functional Near-Infrared Spectroscopy Identifies Changes in Cognitive Workload After Pediatric Concussion

Functional Near-Infrared Spectroscopy Identifies Changes in Cognitive Workload After Pediatric Concussion

Functional Near Infrared Spectroscopy Identifies Changes in Cognitive Workload Following Pediatric Concussion

PURPOSE: To determine if functional near infrared spectroscopy (fNIRS), a noninvasive imaging modality detecting oxygenation changes reflective of cognitive workload, distinguishes physiologic differences between concussion subjects and healthy controls during King-Devick (KD) testing, a rapid number naming task METHODS: We recruited 57 cases, ages 7 to 21 years, 51% female, and 17 controls, ages 10-21 years, 47% female from a subspecialty referral concussion program for this prospective case control study where the subjects performed the KD test while wearing a fNIRS device consisting of a headband which records anterior prefrontal cortex oxygenation changes with 4 optodes at a 4Hz sampling rate. The main outcome measures were KD times, symptom provocation and oxygenation change during KD testing. RESULTS: Concussion subjects demonstrated longer times and greater oxygenation change on fNIRS compared to healthy controls. However, within the group of concussion subjects, KD times did not distinguish between those with and without symptom provocation upon testing. In contrast, fNIRS was able to detect oxygenation change differences between these two subgroups, with the symptomatic group exhibiting greater oxygenation change with testing. CONCLUSIONS: Based on our data, the prolongation of KD times observed following concussion has physiologic correlates with increased cognitive workload. Among subjects with concussion, KD times did not distinguish between those with and those without symptom provocation upon testing. In contrast, fNIRS was able to differentiate between these two subgroups of concussion, with symptomatic subjects exhibiting a pattern of greater cognitive workload compared to asymptomatic. fNIRS has utility in detecting subclinical differences in cognitive workload in concussion. In addition, our data supports the concept that the physiologic basis for symptom provocation in concussion may be related to cognitive overload.Figure

Pupillary Response to Cognitive Demand in Parkinson's Disease: A Pilot Study.

Previous studies have shown that pupillary response, a physiological measure of cognitive workload, reflects cognitive demand in healthy younger and older adults. However, the relationship between cognitive workload and cognitive demand in Parkinson’s disease (PD) remains unclear. The aim of this pilot study was to examine the pupillary response to cognitive demand in a letter-number sequencing (LNS) task between 16 non-demented individuals with PD (age, median (Q1–Q3): 68 (62–72); 10 males) and 10 control participants (age: 63 (59–67); 2 males), matched for age, education, and Montreal Cognitive Assessment (MOCA) scores. A mixed model analysis was employed to investigate cognitive workload changes as a result of incremental cognitive demand for both groups. As expected, no differences were found in cognitive scores on the LNS between groups. Cognitive workload, exemplified by greater pupil dilation, increased with incremental cognitive demand in both groups (p = 0.003). No significant between-group (p = 0.23) or interaction effects were found (p = 0.45). In addition, individuals who achieved to complete the task at higher letter-number (LN) load responded differently to increased cognitive demand compared with those who completed at lower LN load (p < 0.001), regardless of disease status. Overall, the findings indicated that pupillary response reflects incremental cognitive demand in non-demented people with PD and healthy controls. Further research is needed to investigate the pupillary response to incremental cognitive demand of PD patients with dementia compared to non-demented PD and healthy controls.Highlights -Pupillary response reflects cognitive demand in both non-demented people with PD and healthy controls-Although not significant due to insufficient power, non-demented individuals with PD had increased cognitive workload compared to the healthy controls throughout the testing-Pupillary response may be a valid measure of cognitive demand in non-demented individuals with PD-In future, pupillary response might be used to detect cognitive impairment in individuals with PD

FNIRS differentiates cognitive workload between concussed adolescents and healthy controls

fNIRS differentiates cognitive workload between concussed adolescents and healthy controls

Measuring Prefrontal Hemodynamic Responses Using Functional Near-Infrared Spectroscopy During Mobility for a Child With Motor Impairment

Abstract Date Presented 3/31/2017 This study used functional near-infrared spectroscopy (fNIRS) to identify changes in cognitive workload in a child with motor impairment during experiences with robot-assisted mobility. The study provides preliminary support for using fNIRS to measure cognitive workload in novel motor tasks. Primary Author and Speaker: Kelly Cusick Additional Authors and Speakers: Alexandra DiStasi, Stephanie Holowinski, Olivia Fitzpatrick Contributing Authors: Megan Davis, Melody H. Wallace, Sharon A. Stansfield, Carole Dennis, Hélène M. Larin, Nancy Rader, Judith Pena-Shaff

The Use Of Functional Near-Infrared Spectroscopy (fNIRS) For Assessing Cognitive Workload During King-Devick Test After Concussion

PURPOSE: Functional near-infrared spectroscopy (fNIRS), a noninvasive and portable neuroimaging modality that detects changes in blood oxygenation related to human brain function, is a promising tool to address the current lack of objective biomarkers to identify pathophysiologic changes associated with concussion. We sought to determine the utility of fNIRS to detect and differentiate cortical brain activity between concussed and healthy subjects when they performed the King-Devick test. METHODS: We conducted a prospective case-control study of 19 concussed subjects and 9 healthy controls who completed the King-Devick test while wearing an fNIRS headband that recorded anterior prefrontal cortex oxygenation changes with 12 channels/4 optodes at 4Hz sampling rate. Linear mixed model analysis was performed to compare oxygenation changes in the two cohorts. RESULTS: There were significant differences across increasing difficulty of the King-Devick test conditions when comparing concussed subjects with healthy controls in both the left prefrontal cortex (F1,26 = 9.906, p< 0.005) and right prefrontal cortex (F1,25 = 7.965, p< 0.01). Among this pilot cohort, healthy controls showed significantly higher levels of oxygenation changes upon initiation of the King-Devick test compared to concussed subjects, but had decreased oxygenation changes over each successive test card. This pattern was not mirrored in concussed subjects who maintained consistent levels of oxygenation changes in the left prefrontal cortex and increasing levels in the right prefrontal cortex over the course of the test. CONCLUSION: Our preliminary experimental results suggest that fNIRS detects changes in cerebral blood oxygenation between concussed and healthy subjects. Further investigation into the utility of this neuroimaging modality for quantifying changes in cognitive workload after injury and over the course of recovery is warranted.Figure 1: Comparison of oxygenation changes in the right prefrontal cortex between concussed subjects and healthy controls during trials of the King-Devick test (F1.25 = 7.965, p < 0.01).

A multi-measure approach for connecting cognitive workload and automation

Abstract Eye behavior metrics, time of run, and subjective survey results were assessed during human-computer interaction with high, low, and intermediate system autonomy levels. The results of this study are provided as a contribution to knowledge on the relationship between cognitive workload physiology and automation. Research suggests that changes in eye behavior metrics are related to changes in cognitive workload. Few studies have investigated the relationship between eye behavior metrics physiology measures and levels of automation. A within-subjects experiment involving 18 participants who played an open-source real-time strategy game was conducted. Three different versions of the game were developed, each with a unique static autonomy level designed from Sheridan and Verplank's 10 levels of autonomy (levels 2, 4, and 9). NASA-TLX subject survey ratings, time to complete run, and visual fixation rate were found to be significantly different among automation levels. These findings suggest that assessing visual physiology may be a promising indicator for evaluating cognitive workload when interacting with static autonomy levels. This efforts takes us one step closer to using visual physiology as a useful method for evaluating operator workload in almost real-time. Relevance to industry Potential applications of this research include development of software that integrates adaptive automation to improve human-computer task performance for high cognitive workload tasks (Air Traffic Control, aircraft piloting, process control, information analyst, etc.).

Cognitive workload changes for nurses transitioning from a legacy system with paper documentation to a commercial electronic health record

ObjectiveHealthcare institutions worldwide are moving to electronic health records (EHRs). These transitions are particularly numerous in the US where healthcare systems are purchasing and implementing commercial EHRs to fulfill federal requirements. Despite the central role of EHRs to workflow, the cognitive impact of these transitions on the workforce has not been widely studied. This study assesses the changes in cognitive workload among pediatric nurses during data entry and retrieval tasks during transition from a hybrid electronic and paper information system to a commercial EHR. Materials and methodsBaseline demographics and computer attitude and skills scores were obtained from 74 pediatric nurses in two wards. They also completed an established and validated instrument, the NASA-TLX, that is designed to measure cognitive workload; this instrument was used to evaluate cognitive workload of data entry and retrieval. The NASA-TLX was administered at baseline (pre-implementation), 1, 5 and 10 shifts and 4 months post-implementation of the new EHR. ResultsMost nurse participants experienced significant increases of cognitive workload at 1 and 5 shifts after “go-live”. These increases abated at differing rates predicted by participants’ computer attitudes scores (p=0.01). ConclusionsThere is substantially increased cognitive workload for nurses during the early phases (1–5 shifts) of EHR transitions. Health systems should anticipate variability across workers adapting to “meaningful use” EHRs. “One-size-fits-all” training strategies may not be suitable and longer periods of technical support may be necessary for some workers.

Electrode replacement does not affect classification accuracy in dual-session use of a passive brain-computer interface for assessing cognitive workload.

The passive brain-computer interface (pBCI) framework has been shown to be a very promising construct for assessing cognitive and affective state in both individuals and teams. There is a growing body of work that focuses on solving the challenges of transitioning pBCI systems from the research laboratory environment to practical, everyday use. An interesting issue is what impact methodological variability may have on the ability to reliably identify (neuro)physiological patterns that are useful for state assessment. This work aimed at quantifying the effects of methodological variability in a pBCI design for detecting changes in cognitive workload. Specific focus was directed toward the effects of replacing electrodes over dual sessions (thus inducing changes in placement, electromechanical properties, and/or impedance between the electrode and skin surface) on the accuracy of several machine learning approaches in a binary classification problem. In investigating these methodological variables, it was determined that the removal and replacement of the electrode suite between sessions does not impact the accuracy of a number of learning approaches when trained on one session and tested on a second. This finding was confirmed by comparing to a control group for which the electrode suite was not replaced between sessions. This result suggests that sensors (both neurological and peripheral) may be removed and replaced over the course of many interactions with a pBCI system without affecting its performance. Future work on multi-session and multi-day pBCI system use should seek to replicate this (lack of) effect between sessions in other tasks, temporal time courses, and data analytic approaches while also focusing on non-stationarity and variable classification performance due to intrinsic factors.

Psychophysiological response to cognitive workload during symmetrical, asymmetrical and dual-task walking

Walking with a lower limb prosthesis comes at a high cognitive workload for amputees, possibly affecting their mobility, safety and independency. A biocooperative prosthesis which is able to reduce the cognitive workload of walking could offer a solution. Therefore, we wanted to investigate whether different levels of cognitive workload can be assessed during symmetrical, asymmetrical and dual-task walking and to identify which parameters are the most sensitive. Twenty-four healthy subjects participated in this study. Cognitive workload was assessed through psychophysiological responses, physical and cognitive performance and subjective ratings. The results showed that breathing frequency and heart rate significantly increased, and heart rate variability significantly decreased with increasing cognitive workload during walking (p<.05). Performance measures (e.g., cadence) only changed under high cognitive workload. As a result, psychophysiological measures are the most sensitive to identify changes in cognitive workload during walking. These parameters reflect the cognitive effort necessary to maintain performance during complex walking and can easily be assessed regardless of the task. This makes them excellent candidates to feed to the control loop of a biocooperative prosthesis in order to detect the cognitive workload. This information can then be used to adapt the robotic assistance to the patient’s cognitive abilities.