# Quantitative Tactile Assessment of Human Manual Dexterity

> **NIH NIH R21** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2020 · $209,392

## Abstract

Manual dexterity enables humans to manipulate small objects with our fingers, perform highly skilled tasks
as well as simple activities of daily living. These actions require independent finger movements, and precise
control of the direction and magnitude of fingertip forces such as those involved in grasping objects. We
grasp objects of various textures, weights, and shapes by adapting our fingertip forces to friction at the
grasping surface, the weight of the object, and its shape. The grip force must be optimized to prevent
excessive squeezing of the object (wasted force and/or object damage) or slippage of the object from grasp
(and possible breakage) due to insufficient, weak forces. The sense of touch is used perceive friction at the
object surface; without tactile feedback humans tend to use too much force when grasping, or apply
insufficient forces. In this study we use high-resolution 3D printing to create textured surfaces whose
physical dimensions are specified and quantified in psychophysical tests. We propose to quantify and
analyze manual dexterity using a grasp-and-lift task in which we measure the effects of load and surface
texture on performance in healthy human adults of ages 18-80, and in subjects with central and/or
peripheral neurological impairments. These experiments will provide quantitative metrics of manual dexterity
and force control in young, middle-aged, and elderly subjects that can serve as baseline values for
evaluating treatment and rehabilitation therapies following stroke, or peripheral nerve injury, as well as the
well-known reduction in hand function as a result of aging.

## Key facts

- **NIH application ID:** 10017141
- **Project number:** 5R21AG064452-02
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** ESTHER P. GARDNER
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $209,392
- **Award type:** 5
- **Project period:** 2019-09-15 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10017141

## Citation

> US National Institutes of Health, RePORTER application 10017141, Quantitative Tactile Assessment of Human Manual Dexterity (5R21AG064452-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10017141. Licensed CC0.

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