HiTEC: a connectionist model of the interaction between perception and action planning.

Increasing evidence suggests that perception and action planning do not represent separable stages of a unidirectional processing sequence, but rather emerging properties of highly interactive processes. To capture these characteristics of the human cognitive system, we have developed a connectionist model of the interaction between perception and action planning: HiTEC, based on the Theory of Event Coding (Hommel et al. in Behav Brain Sci 24:849-937, 2001). The model is characterized by representations at multiple levels and by shared representations and processes. It complements available models of stimulus-response translation by providing a rationale for (1) how situation-specific meanings of motor actions emerge, (2) how and why some aspects of stimulus-response translation occur automatically and (3) how task demands modulate sensorimotor processing. The model is demonstrated to provide a unitary account and simulation of a number of key findings with multiple experimental paradigms on the interaction between perception and action such as the Simon effect, its inversion (Hommel in Psychol Res 55:270-279, 1993), and action-effect learning.

A dynamic quality assessment tool for laparoscopic hysterectomy to measure surgical outcomes.

BACKGROUND: The current healthcare system has an urgent need for tools to measure quality. A wide range of quality indicators have been developed in an attempt to differentiate between high-quality and low-quality healthcare processes. However, one of the main issues of currently used indicators is the lack of case-mix correction and improvement possibilities. Case-mix is defined as specific (patient) characteristics that are known to potentially affect (surgical) outcome. If these characteristics are not taken into consideration, comparisons of outcome among healthcare providers may not be valid OBJECTIVE: To develop and test a quality assessment tool for laparoscopic hysterectomy, which can serve as a new outcome quality indicator STUDY DESIGN: This is a prospective international multicenter implementation study. A web-based application (.www.qusum.org) was developed with three main goals: to measure the surgeon's performance using three primary outcomes (blood loss, operative time, and complications); to provide immediate individual feedback using cumulative Observed-minus-Expected graphs; and to detect consistently suboptimal performance after correcting for case-mix characteristics. All gynecologists who perform laparoscopic hysterectomies were requested to register their procedures in the application. A patient safety risk factor checklist was used by the surgeon for reflection. Thereafter, a prospective implementation study was performed, and the application was tested using a survey that included the System Usability Scale. RESULTS: A total of 2066 laparoscopic hysterectomies were registered by 81 gynecologists. Mean operative time was 100±39 minutes, blood loss 127±163ml, and the complication rate 6.1%. The overall survey response rate was 75%, and the mean System Usability Scale was 76.5±13.6, which indicates that the application was good to excellent. The majority of surgeons reported that the application made them more aware of their performance, the outcomes, and patient safety, and they noted that the application provided motivation for improving future performance. CONCLUSIONS: We report the development and test of a real-time, dynamic quality assessment tool for measuring individual surgical outcome for laparoscopic hysterectomy. Importantly, this tool provides opportunities for improving surgical performance. Our study provides a foundation for helping clinicians develop evidence-based quality indicators for other surgical procedures.

A dynamic quality assessment tool for laparoscopic hysterectomy to measure surgical outcomes.

BACKGROUND: The current health care system has an urgent need for tools to measure quality. A wide range of quality indicators have been developed in an attempt to differentiate between high-quality and low-quality health care processes. However, one of the main issues of currently used indicators is the lack of case-mix correction and improvement possibilities. Case-mix is defined as specific (patient) characteristics that are known to potentially affect (surgical) outcome. If these characteristics are not taken into consideration, comparisons of outcome among health care providers may not be valid. OBJECTIVE: The objective of the study was to develop and test a quality assessment tool for laparoscopic hysterectomy, which can serve as a new outcome quality indicator. STUDY DESIGN: This is a prospective, international, multicenter implementation study. A web-based application was developed with 3 main goals: (1) to measure the surgeon's performance using 3 primary outcomes (blood loss, operative time, and complications); (2) to provide immediate individual feedback using cumulative observed-minus-expected graphs; and (3) to detect consistently suboptimal performance after correcting for case-mix characteristics. All gynecologists who perform laparoscopic hysterectomies were requested to register their procedures in the application. A patient safety risk factor checklist was used by the surgeon for reflection. Thereafter a prospective implementation study was performed, and the application was tested using a survey that included the System Usability Scale. RESULTS: A total of 2066 laparoscopic hysterectomies were registered by 81 gynecologists. Mean operative time was 100 ± 39 minutes, blood loss 127 ± 163 mL, and the complication rate 6.1%. The overall survey response rate was 75%, and the mean System Usability Scale was 76.5 ± 13.6, which indicates that the application was good to excellent. The majority of surgeons reported that the application made them more aware of their performance, the outcomes, and patient safety, and they noted that the application provided motivation for improving future performance. CONCLUSION: We report the development and test of a real-time, dynamic, quality assessment tool for measuring individual surgical outcome for laparoscopic hysterectomy. Importantly, this tool provides opportunities for improving surgical performance. Our study provides a foundation for helping clinicians develop evidence-based quality indicators for other surgical procedures.

How Task Goals Mediate the Interplay between Perception and Action.

Theories of embodied cognition suppose that perception, action, and cognition are tightly intertwined and share common representations and processes. Indeed, numerous empirical studies demonstrate interaction between stimulus perception, response planning, and response execution. In this paper, we present an experiment and a connectionist model that show how the Simon effect, a canonical example of perception-action congruency, can be moderated by the (cognitive representation of the) task instruction. To date, no representational account of this influence exists. In the experiment, a two-dimensional Simon task was used, with critical stimuli being colored arrows pointing in one of four directions (backward, forward, left, or right). Participants stood on a Wii balance board, oriented diagonally toward the screen displaying the stimuli. They were either instructed to imagine standing on a snowboard or on a pair of skis and to respond to the stimulus color by leaning toward either the left or right foot. We expected that participants in the snowboard condition would encode these movements as forward or backward, resulting in a Simon effect on this dimension. This was confirmed by the results. The left-right congruency effect was larger in the ski condition, whereas the forward-backward congruency effect appeared only in the snowboard condition. The results can be readily accounted for by HiTEC, a connectionist model that aims at capturing the interaction between perception and action at the level of representations, and the way this interaction is mediated by cognitive control. Together, the empirical work and the connectionist model contribute to a better understanding of the complex interaction between perception, cognition, and action.

A computational model of perception and action for cognitive robotics.

Robots are increasingly expected to perform tasks in complex environments. To this end, engineers provide them with processing architectures that are based on models of human information processing. In contrast to traditional models, where information processing is typically set up in stages (i.e., from perception to cognition to action), it is increasingly acknowledged by psychologists and robot engineers that perception and action are parts of an interactive and integrated process. In this paper, we present HiTEC, a novel computational (cognitive) model that allows for direct interaction between perception and action as well as for cognitive control, demonstrated by task-related attentional influences. Simulation results show that key behavioral studies can be readily replicated. Three processing aspects of HiTEC are stressed for their importance for cognitive robotics: (1) ideomotor learning of action control, (2) the influence of task context and attention on perception, action planning, and learning, and (3) the interaction between perception and action planning. Implications for the design of cognitive robotics are discussed.