The effects of impairment severity on cursor control for youths with cerebral palsy

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Sub-movement evaluation

The measures of sub-movement are as follows: number of sub-movements, number of sub-movements following final target entry (SMFFTE), number of slip-offs (target re-entry), sub-movement with a maximum peak speed, number of counter-productive submovements, and number of sub-movements (threshold speed is 0.5 pixels/millisecond).

Accuracy measures

The measures of accuracy are as follows: trajectory distance (TRD) (Equation 4.2), overshoot distance (OS) (Equation 4.2), opposite direction (OD) (Equation 4.2), start-end click point amplitude (A‟) (Equation 4.2), curvature index (CI) (Equation 4.2), linearity index (LI) (Equation 4.3), start-end point angle (SEA) (Equation 4.3), angular deviation (AD) (Equation 4.3), average angular deviation, the index of vertical component (IVC), the index of horizontal component (IHC), and the index of diagonal component (IDC). Fig. 4.5 shows a visual definition of the accuracy measures (Equation 4.2 and Equation 4.3).

THE PROPOSED MODEL

The fundamental idea behind this proposed model was to join the Shannon formulation of ID (Equation 2.4) of Fitts‟s law with the most important path evaluation measures to formulate an equation to predict movement time (MT). This model is based on the inclusion of both system influence and human influences, similar to the SH-model [30]. System influence is evaluated by the pointing task condition (the amplitude between targets and the target width), while the number of erroneous clicks is an example of human behaviour affecting task performance. In previous research [27, 38, 42-44, 48-50, 52-54], 40 different path evaluation measures were identified as possible contributors to movement and submovement times.
The most important path evaluation measures that relate to movement time were determined using an automatic linear modelling technique. It was found that the best features of human error that significantly affect movement time were the number of erroneous clicks (EC), the number of sub-movements (NS), the curvature index (CI), the number of slip-offs (NSO), and average speed (AS). These were used in the development of the new model.

Apparatus

TD participants: Participants were seated comfortably on a desk chair in a normally lit room whilst they completed computer mouse pointing tasks at a desk. The experiment was conducted on a Dell desktop machine with a 2.4 GHz Intel® Core™ 2 Quad CPU with 2 GB of RAM running 64-bit Windows 7 Enterprise. The pointer speed (C-D gain) was set to 10 as normal. The screen used was at a resolution of 1280 × 1024 pixels (51 x 33 centimetres) with a refresh rate of 60 Hz. The pointing device type was a standard USB optical mouse. The resolution of the screen was 96 pixels per inch (DPI). The average horizontal distance between the screen and a participant‟s face ranged between 50 and 60 centimetres.
Individuals with CP: Participants sat at a desk (some of them in a wheelchair) and completed pointing tasks with a computer mouse under normal lighting conditions. The experiment was conducted on an HP laptop machine with a 2.2 GHz AMD Turion™ X2 Ultra Dual-Core Mobile ZM-82 with 3 GB of RAM running 32-bit Windows 7 Enterprise. The pointer speed (control and display gain) was set to 10 as normal. The screen used was at a resolution of 1280 × 800 pixels (35 x 24 centimetres) with a refresh rate of 60 Hz. The pointing device type was a standard USB optical mouse (manufactured by Dell). The resolution of the screen was 96 pixels per inch (DPI). The average distance between the screen and participants ranged between 50 and 60 centimetres.

READ Data Presentation and Data Analysis

1. Introduction
1.1. Background and need for the study .
1.1.1. Cerebral palsy
1.1.2. Human-computer interface (HCI) design
1.2. Research Questions and Hypotheses
1.3. Thesis structure
2. Literature review and theoretical framework
2.1. Theoretical FrameWork
2.1.1. The iterative correction model
2.1.2. The impulse variability model
2.1.3. The optimized initial impulse model
2.1.4. Point-and-click tasks (tapping tasks)
2.1.5. Fitts’s law
2.1.6. Ballistic factor
2.1.7. Fitts’s law and ballistic movement adherence by youths with CP
2.1.8. System-human (SH) model .
2.2. Path Evaluation Measures
2.3. New Accuracy measures Proposed
2.4. Critical Evaluation of path measures .
2.5. Pointing facilitation Techniques .
3. The effects of impairment severity on cursor control for youths with cerebral palsy
3.1. Questions and Hypotheses
3.2. Participants
3.3. Computer Task Test
3.4. Results
3.5. Discussio
3.6. Contribution
4. Software Design .
4.1. Review of common tools
4.2. Platform Capabilities
4.3. Experiment Input and experimental protocol
4.4. Data Analysis .
5. A Non-linear Model for Pointing Task Evaluation Based on Both System and Human Effects
5.1. Question and Hypothesis
5.2. The Proposed Model
5.3. Empirical Validation of proposed Model .
5.4. Results and Analysis .
5.5. Discussion
5.6. Contribution
5.7. Conclusion
6. A dynamic Adjustments of Control- Display Gain Based On Curvature Index
6.1. Question and Hypothesis
6.2. The proposed algorithm
6.3. Empirical Validation and examination of proposed algorithm
6.4. Results and analysis
6.5. Discussion
6.6. Study Limitation
6.7. Conclusion
6.8. Contribution
6.9. Future Work
7. General Discussion