Precision grasping in people : a detailed analysis of the central and external properties of precision grasping from the young to the elderly
Bibliographic record
Abstract
To understand the grasping abnormalities in Parkinson's or stroke patients, normal grasping must be examined, and whether that normality is determined by biological factors or experiential influence must also be considered.The purpose of this thesis is to determine what normal variations of precision grasping exist in healthy, normal adults, children and elderly people.Using Eshkol-Wachmann Movement Notation, five types of contact strategies were interpolated, based on the digit that contacts the object first, and whether that digit dragged or stabilized the object for grasping.Each contact strategy was associated with an ideal graphical representation of the thumb and index finger velocities.There were seven variations of purchase patterns, based on the digits used to contact the objects, and four variations of postures of the non-grasping digits on top of the five contact strategies.Object size affected purchase pattern preference: smaller objects elicited the pincer grasp more than the larger objects.The purchase pattern distribution of variation is similar in adults and children, although children exhibit an extra purchase pattern, and older adults exhibit less variation purchase patterns.The findings from this thesis suggest that central factors, such as gender and handedness, as well as external factors, such as size of the object, determine individual preference of grasping.The loss of variation with age can be attributed to the developing corticospinal tract in children as well as the deterioration of normal hand function in the elderly.iii ACKNOWLEDGEMENTS My experience at the University of Lethbridge has been life-altering these past two years.Time flew by thanks to friends and mentors I have met since I arrived.Working with Dr. Ian Whishaw has been an honour, and I appreciate the chance that he has given me to work at the Canadian Centre for Behavioural Neuroscience.He has taught me about the academic world, science, writing, and most of all, he has taught me to be independent in life and in thought.The more the rumours spread of his eccentricity, the more I have come to appreciate his insights and breadth of knowledge.He has given me confidence in my strengths and abilities, and helped me acknowledge my weaknesses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".