Chad L. Stephens

Biocybernetic Adaptation as Biofeedback Training Method

A method developed for adapting an automated flight control system to user state has been applied to the process of biofeedback training. This repurposing enables alternative mechanisms for delivering physiological information feedback to the trainee via a method referred to as physiological modulation. These mechanisms employ reinforcement principles to motivate adherence to the biofeedback training regime, to foster interactions among users and to enhance the experience of immersion in video game entertainment. The approach has implications for a broader dissemination of biofeedback training. This chapter will introduce the traditional biofeedback training method and its clinical applications, followed by a discussion of how biocybernetic adaptation can be applied to the biofeedback training method. This will be followed by a description of different methods of realising this self-regulation technology and where the technology may go in the future.

Interpersonal biocybernetics: connecting through social psychophysiology

One embodiment of biocybernetic adaptation is a human-computer interaction system designed such that physiological signals modulate the effect that control of a task by other means, usually manual control, has on performance of the task. Such a modulation system enables a variety of human-human interactions based upon physiological self-regulation performance. These interpersonal interactions may be mixes of competition and cooperation for simulation training and/or videogame entertainment.

Quantifying pilot contribution to flight safety for normal and non-normal airline operations

Accident statistics cite the flight crew as a causal factor in over 60% of accidents involving transport category airplanes. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. No data currently exists that quantifies the contribution of the flight crew in this role. Neither does data exist for how often the flight crew handles non-normal procedures or system failures on a daily basis in the National Airspace System. A pilot-in-the-loop high fidelity motion simulation study was conducted by the NASA Langley Research Center in partnership with the Federal Aviation Administration (FAA) to evaluate the pilots contribution to flight safety during normal flight and in response to aircraft system failures. Eighteen crews flew various normal and non-normal procedures over a two-day period and their actions were recorded in response to failures. To quantify the humans contribution, crew complement was used as the experiment independent variable in a between-subjects design. Pilot actions and performance when one of the flight crew was impaired were also recorded for comparison against the nominal two-crew operations. This paper details a portion of the results of this study.

Test and Evaluation Metrics of Crew Decision-Making And Aircraft Attitude and Energy State Awareness

NASA has established a technical challenge, under the Aviation Safety Program, Vehicle Systems Safety Technologies project, to improve crew decision-making and response in complex situations. The specific objective of this challenge is to develop data and technologies which may increase a pilots (crews) ability to avoid, detect, and recover from adverse events that could otherwise result in accidents/incidents. Within this technical challenge, a cooperative industry-government research program has been established to develop innovative flight deck-based counter-measures that can improve the crews ability to avoid, detect, mitigate, and recover from unsafe loss-of-aircraft state awareness - specifically, the loss of attitude awareness (i.e., Spatial Disorientation, SD) or the loss-of-energy state awareness (LESA). A critical component of this research is to develop specific and quantifiable metrics which identify decision-making and the decision-making influences during simulation and flight testing. This paper reviews existing metrics and methods for SD testing and criteria for establishing visual dominance. The development of Crew State Monitoring technologies - eye tracking and other psychophysiological - are also discussed as well as emerging new metrics for identifying channelized attention and excessive pilot workload, both of which have been shown to contribute to SD/LESA accidents or incidents.

Automation and Inattentional Blindness in a Simulated Flight Task

The study reported herein is a subset of a larger investigation on the role of automation in the context of single pilot aviation operations. This portion of the study focused on the relationship between automation and inattentional blindness (IB) occurrences for a runway incursion. The runway incursion critical stimulus was directly relevant to primary task performance. Participants performed the final five minutes of a landing scenario in one of three automation conditions (autopilot, autothrottle, and manual). Sixty non-pilot participants completed this study and 70% (42 of 60) failed to detect the runway incursion critical stimulus. Participants in the partial automation condition were significantly more likely to detect the runway incursion when compared to those in the full automation condition. The odds of participant detection in the full automation condition did not significantly vary from the manual condition. Participants that detected the runway incursion did not have significantly higher scores on any component of the NASA-TLX compared to those who failed to detect. The relationship demonstrated between automation condition and IB occurrence indicates the role of automation in operational attention detriment.

An assessment of reduced crew and single pilot operations in commercial transport aircraft operations

Future reduced crew operations or even single pilot operations for commercial airline and on-demand mobility applications are an active area of research. These changes would reduce the human element and thus, threaten the precept that “a well-trained and well-qualified pilot is the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system.” NASA recently completed a pilot-in-the-loop high fidelity motion simulation study in partnership with the Federal Aviation Administration (FAA) attempting to quantify the pilots contribution to flight safety during normal flight and in response to aircraft system failures. Crew complement was used as the experiment independent variable in a between-subjects design. These data show significant increases in workload for single pilot operations, compared to two-crew, with subjective assessments of safety and performance being significantly degraded as well. Nonetheless, in all cases, the pilots were able to overcome the failure mode effects in all crew configurations. These data reflect current-day flight deck equipage and help identify the technologies that may improve two-crew operations and/or possibly enable future reduced crew and/or single pilot operations.

Biocybernetic Adaptation Strategies: Machine Awareness of Human Engagement for Improved Operational Performance

Human operators interacting with machines or computers continually adapt to the needs of the system ideally resulting in optimal performance. In some cases, however, deteriorated performance is an outcome. Adaptation to the situation is a strength expected of the human operator which is often accomplished by the human through self-regulation of mental state. Adaptation is at the core of the human operator’s activity, and research has demonstrated that the implementation of a feedback loop can enhance this natural skill to improve training and human/machine interaction. Biocybernetic adaptation involves a “loop upon a loop,” which may be visualized as a superimposed loop which senses a physiological signal and influences the operator’s task at some point. Biocybernetic adaptation in, for example, physiologically adaptive automation employs the “steering” sense of “cybernetic,” and serves a transitory adaptive purpose – to better serve the human operator by more fully representing their responses to the system. The adaptation process usually makes use of an assessment of transient cognitive state to steer a functional aspect of a system that is external to the operator’s physiology from which the state assessment is derived. Therefore, the objective of this paper is to detail the structure of biocybernetic systems regarding the level of engagement of interest for adaptive systems, their processing pipeline, and the adaptation strategies employed for training purposes, in an effort to pave the way towards machine awareness of human state for self-regulation and improved operational performance.

Uncertainty in Heart Rate Complexity Metrics caused by R-peak Perturbations

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into complex decision models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments and HRC measurements to characteristize the influence of noise on the HRC measure by altering the fiducial point of the Rpeak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.

Repeated Induction of Inattentional Blindness in a Simulated Aviation Environment

The study reported herein is a subset of a larger investigation on the role of automation in the context of the flight deck and used a fixed-based, human-in-the-loop simulator. This portion explored the relationship between automation and inattentional blindness (IB) occurrences in repeated induction using two types of runway incursions directly relevant to primary task performance. Sixty non-pilot participants performed the final five minutes of a landing scenario twice in one of three automation condition: full automation (FA), partial automation (PA), and no automation (NA). The first induction resulted in a 70% detection failure rate and the second induction resulted in a 50% detection failure rate. Detection improved in all conditions. IB group membership (IB vs. Detection) in the FA condition showed the most improvement and rated the Mental Demand and Effort subscales of the NASA-TLX significantly higher for Time 2 compared Time 1. Participants in the FA condition used the experience of IB exposure to reallocate attentional resources and improve task performance. These findings support the role of engagement in attention detriment and the consideration of attentional failure causation to select appropriate mitigation strategies.

Mild Normobaric Hypoxia Exposure for Human-Autonomy System Testing

An experiment investigated the impact of normobaric hypoxia induction on aircraft pilot performance to specifically evaluate the use of hypoxia as a method to induce mild cognitive impairment to explore human-autonomous systems integration opportunities. Results of this exploratory study show that the effect of 15,000 feet simulated altitude did not induce cognitive deficits as indicated by performance on written, computer-based, or simulated flight tasks. However, the subjective data demonstrated increased effort by the human test subject pilots to maintain equivalent performance in a flight simulation task. This study represents current research intended to add to the current knowledge of performance decrement and pilot workload assessment to improve automation support and increase aviation safety.