HPI Goals

HPI has an ambitious, exciting, and synergistic set of long-term goals that guide our selection of short-term projects in which we become involved. These short-term projects not only provide the opportunity to achieve step-wise progress toward our longer-term goals, but typically also yield results (e.g., findings, instruments, procedures, etc.) that have immediate utility to one or more research sponsors.

While our original work focusing on measurement (1979-1984) was motivated by needs first in neurology and then more generally in rehabilitation, the inklings of the systems engineering approach (that has since become one of our most visible trademarks) attracted interest in our work from other fields. These were fields where there was nothing particularly "wrong" with the humans involved; i.e., they were either healthy (e.g., in the ergonomics field) or specially skilled (e.g., athletes, surgeons, etc.). Early on, we characterized our approach as being "disease and injury independent", which was in direct contrast to most of what was found in the rehabilitation research literature. The addition of healthy and specially skilled humans to the mix helped shape our approach; i.e., we hypothesized that there should be one approach that would work with all humans. This notion has proven to be invaluable to our efforts over the long-term.

In formulating the HPI mission, it was desired to communicate our intention to address the most general problems (i.e., those that cut across diseases, injuries, different jobs, worker types, athletes, tasks, etc.). It was our observation that few people recognized these "general problems" and this, in part, has impeded progress in the field. This focus on "the general problems" was in large part guided by the sense that we had gained some insight in "the general solutions". One aspect of this was recognizing that the architecture of the human system is not only "the" common denominator that cuts across all disease and injuries, but also "the" common denominator that cuts across all jobs, sport endeavors, etc.

The long-term goals are such that they can be (and have been) pursued in parallel.

HPI's Long-Term Goals

Details (click icon) Goal Statement

GOAL 1: PERFORMANCE THEORY

To create or identify a quantitative cause-and-effect modeling strategy that can explain with reasonable fidelity the interface of any human system to any any task.

GOAL 2: MEASUREMENT TOOLS

To identify, develop, and/or foster the development of appropriate measurement concepts and instruments to quantitatively characterize human systems (e.g., performance capacities) and tasks (i.e., demands) to obtain numerical parameters for use in models described in Goal 1.

GOAL 3: ANALYSIS TOOLS

To develop, or foster the development of, a comprehensive computer-based tool or set of tools to support human-task interface analyses and predictions for use by both researchers and practitioners.

GOAL 4: APPLICATIONS RESEARCH- PERFORMANCE ENHANCEMENT

To identify and conduct projects that address selected, non-trivial application problems and demonstrate how to employ models, measurements, and computer-based tools to solve everyday human performance problems encountered by a wide range of practitioners. These projects are aimed at enhancing performance of either the practitioners - or those who they serve.

GOAL 5: DISSEMINATION

To enable practitioners across a wide-range of different fields to carry out high-quality (objective, accurate, etc.) problem solving and decision-making tasks related to human performance issues based on a common set of principles and methodology.

HPI's Long-Term Goals
Details (click icon)	Goal Statement
	GOAL 1: PERFORMANCE THEORY To create or identify a quantitative cause-and-effect modeling strategy that can explain with reasonable fidelity the interface of any human system to any any task.
	GOAL 2: MEASUREMENT TOOLS To identify, develop, and/or foster the development of appropriate measurement concepts and instruments to quantitatively characterize human systems (e.g., performance capacities) and tasks (i.e., demands) to obtain numerical parameters for use in models described in Goal 1.
	GOAL 3: ANALYSIS TOOLS To develop, or foster the development of, a comprehensive computer-based tool or set of tools to support human-task interface analyses and predictions for use by both researchers and practitioners.
	GOAL 4: APPLICATIONS RESEARCH- PERFORMANCE ENHANCEMENT To identify and conduct projects that address selected, non-trivial application problems and demonstrate how to employ models, measurements, and computer-based tools to solve everyday human performance problems encountered by a wide range of practitioners. These projects are aimed at enhancing performance of either the practitioners - or those who they serve.
	GOAL 5: DISSEMINATION To enable practitioners across a wide-range of different fields to carry out high-quality (objective, accurate, etc.) problem solving and decision-making tasks related to human performance issues based on a common set of principles and methodology.

Our mission is to pursue basic and applied research in measurement, understanding (through development of models and validation experiments), and enhancement of human performance. The focus of this statement is "human performance" - and we have chosen to interpret this phrase to mean "a human executing a task" or, in other words, the "interface of a human to a task". The mission statement also refers to three aspects of human performance: measurement, modeling, and enhancement. The use of these terms deserves further elaboration.

Measurement

Modeling

Enhancement

"Measurement" has been the key to scientific progress in many fields. We define measurement here to include measurement of performance and capacity for performance, as well as any ancillary attributes necessary to understand performance (such as attributes of structure). Furthermore, we understand measurement to be valuable at different hierarchical levels (e.g., the "elbow flexor" subsystem vs. measuring how well a person can drive - or the "driving system"). "Modeling" is viewed to be synonymous with "understanding". We seek the ability to relate measurements made at one hierarchical level to another level within the human system. Reliable models provide the ability to explain and to predict. We envision, for example, models that tell us how much of a given performance capacity (e.g., strength, movement speed, visual information processing speed, positioning accuracy, etc. - of selected subsystems) is "required" to achieve a given level of performance in some high level task of interest (e.g., playing the cello, operating a robot, working as an engineer, etc.). Prior to some of our theoretical developments, it was not possible to state this vision clearly. The development of all such models is beyond the scope of a single institution. Based on our findings, however, we believe that it is feasible to create and demonstrate a methodology for the development of such models and to demonstrate their utility. In doing so, we hope to lead others to take on model development for specific applications. Finally, the term "enhancement" means improvement of performance relative to some initial reference point. There is much good work regarding what it takes to enhance human performance in certain areas. However, in fields such as rehabilitation, sports, and music there remains a considerable need to know how to efficiently enhance performance.

Measurements give insight into models and then provide the means for developing and implementing models. Models lead to new understanding and this new understanding will, in turn, no doubt lead to better methods for enhancing performance.

Our mission is to pursue basic and applied research in measurement, understanding (through development of models and validation experiments), and enhancement of human performance. The focus of this statement is "human performance" - and we have chosen to interpret this phrase to mean "a human executing a task" or, in other words, the "interface of a human to a task". The mission statement also refers to three aspects of human performance: measurement, modeling, and enhancement. The use of these terms deserves further elaboration.

Measurement	Modeling	Enhancement
"Measurement" has been the key to scientific progress in many fields. We define measurement here to include measurement of performance and capacity for performance, as well as any ancillary attributes necessary to understand performance (such as attributes of structure). Furthermore, we understand measurement to be valuable at different hierarchical levels (e.g., the "elbow flexor" subsystem vs. measuring how well a person can drive - or the "driving system").	"Modeling" is viewed to be synonymous with "understanding". We seek the ability to relate measurements made at one hierarchical level to another level within the human system. Reliable models provide the ability to explain and to predict. We envision, for example, models that tell us how much of a given performance capacity (e.g., strength, movement speed, visual information processing speed, positioning accuracy, etc. - of selected subsystems) is "required" to achieve a given level of performance in some high level task of interest (e.g., playing the cello, operating a robot, working as an engineer, etc.). Prior to some of our theoretical developments, it was not possible to state this vision clearly. The development of all such models is beyond the scope of a single institution. Based on our findings, however, we believe that it is feasible to create and demonstrate a methodology for the development of such models and to demonstrate their utility. In doing so, we hope to lead others to take on model development for specific applications.	Finally, the term "enhancement" means improvement of performance relative to some initial reference point. There is much good work regarding what it takes to enhance human performance in certain areas. However, in fields such as rehabilitation, sports, and music there remains a considerable need to know how to efficiently enhance performance.
Measurements give insight into models and then provide the means for developing and implementing models. Models lead to new understanding and this new understanding will, in turn, no doubt lead to better methods for enhancing performance.