Feedback Control Based on Digital Sensors

One way to use digital sensors to adjust the force output would be to engage these sensors in feedback

Too weak Adequate Too strong Figure 1

When manipulating objects grasped with a precision grip, we must carefully control the balance between grip force, normal to the contact surfaces, and load force tangential to the grasp surfaces. If grip force is too weak for a given load force, we risk having the object slip from our grasp. If grip force is too strong, we may crush the object or damage our hand and we waste energy.

loops. However, such loops imply large time delays. These time delays arise from impulse conduction time in peripheral nerves, conduction and processing time in the central nervous system, and the inherent sluggishness of muscles. In humans, these factors sum to at least 100 msec for the generation of a significant force response. Consequently, closed-loop feedback is not effective for rapid movement involving frequencies above 1 Hz. In natural manipulation tasks, movement frequency components up to 5 Hz can be observed. Thus, feedback control alone cannot sup port control of grip force for grasp stability in these movements.

Despite these control limitations, feedback control is essential in certain types of manipulative tasks. For example, feedback control is required in reactive tasks in which we restrain "active" objects that generate unpredictable load forces tangential to the grip surfaces. Examples of tasks in which we must deal with active objects are holding a dog's leash, restraining a child by holding his or her arm, or operating power tools. Consider the situation depicted in Fig. 2A

Figure 2 Peripheral afferent and reactive grip force responses to unpredictable loading of the precision grip by a pulling force. (A) The subject grasped the manipulandum with the tips of the thumb and index finger contacting parallel grip surfaces 25 mm apart. The force motor could deliver load forces pulled away from or pushed toward the hand. The grip and load forces, normal and tangential to the grip surfaces, respectively, and the position of the manipulandum were recorded. Afferent activity was recorded from the median nerve, with percutaneously inserted tungsten needle electrodes impaling the nerve about 10 cm proximal to the elbow. (B) Grip responses and average discharge rate of 10 FA I sensors to 2 N pulling loads delivered to the receptor-bearing digit at 2 N/sec (dashed lines) and 8 N/sec (solid lines). The two traces of single unit recordings are examples of responses in a single FA I sensor during load trials at 8 N/sec (upper trace) and 2 N/sec (lower trace). (C) Grip response and average discharge rate of 19 muscle afferents located in the long flexor muscles of the index, middle, or ring finger to 2.0 N pulling loads delivered at 4 N/sec. The single unit recordings are examples of responses in two different muscle spindle afferents. (B and C) The averages of forces and discharge rates are synchronized to the onset of the loading ramp; discharge rate represents average instantaneous frequency (adapted with permission from Macefield, V. G., Hager-Ross, C., and Johansson, R. S., Exp. Brain Res. 108, 155-171, 1996; and Macefield, V. G., and Johansson, R. S., Exp. Brain Res. 108, 172-184, 1996. Copyright © 1996 by Springer-Verlag).

Figure 2 Peripheral afferent and reactive grip force responses to unpredictable loading of the precision grip by a pulling force. (A) The subject grasped the manipulandum with the tips of the thumb and index finger contacting parallel grip surfaces 25 mm apart. The force motor could deliver load forces pulled away from or pushed toward the hand. The grip and load forces, normal and tangential to the grip surfaces, respectively, and the position of the manipulandum were recorded. Afferent activity was recorded from the median nerve, with percutaneously inserted tungsten needle electrodes impaling the nerve about 10 cm proximal to the elbow. (B) Grip responses and average discharge rate of 10 FA I sensors to 2 N pulling loads delivered to the receptor-bearing digit at 2 N/sec (dashed lines) and 8 N/sec (solid lines). The two traces of single unit recordings are examples of responses in a single FA I sensor during load trials at 8 N/sec (upper trace) and 2 N/sec (lower trace). (C) Grip response and average discharge rate of 19 muscle afferents located in the long flexor muscles of the index, middle, or ring finger to 2.0 N pulling loads delivered at 4 N/sec. The single unit recordings are examples of responses in two different muscle spindle afferents. (B and C) The averages of forces and discharge rates are synchronized to the onset of the loading ramp; discharge rate represents average instantaneous frequency (adapted with permission from Macefield, V. G., Hager-Ross, C., and Johansson, R. S., Exp. Brain Res. 108, 155-171, 1996; and Macefield, V. G., and Johansson, R. S., Exp. Brain Res. 108, 172-184, 1996. Copyright © 1996 by Springer-Verlag).

in which an individual grasps an object attached to a force motor using a precision grip with the tips of the thumb and index finger on opposing vertical surfaces. The motor is used to generate increasing load forces (tangential to the grip surfaces) that are unpredictable in terms of onset time, amplitude, and direction (loading and unloading). To prevent the object from slipping, people automatically respond to increases in tangential load by increasing grip force normal to the grip surfaces in parallel with the load force changes (see load and grip force signals in Figs. 2B and 2C). When the load stops increasing, the grip force also stops increasing and may decrease slightly. Importantly, the changes in grip force lag behind the load force changes because they are reactively generated. A reactive grip response is initiated after a delay of approximately 100 msec but this varies with the load force rate. Because of this time lag, the object will slip from grasp unless the background grip force prior to a load increase is strong enough to meet the initial load increase. Indeed, following slips and trials with a high rate of load force increases, people learn to increase the initial background grip force as an adaptation to the expected range of loadings.

Figure 2A also shows signals, recorded using the technique of microneurography, from single nerve fibers of the median nerve that supply cutaneous, muscle, and joint sensors. Experiments with cutaneous anesthesia have demonstrated that reactive fingertip force responses are driven primarily by digital cutaneous inputs. Signals from fast adapting (FA I) cutaneous afferents seem most important, but slowly adapting cutaneous afferents may also contribute. As illustrated in Fig. 2B, the intensity of the cutaneous afferent responses is scaled by the rate of load force increase, and the afferent responses commence before the onset of the grip response. Furthermore, the size and duration of the grip force increase is scaled with the intensity and duration of the afferent response. This scaling is an attractive feature for feedback-based control.

Whereas cutaneous afferents contribute to the initiation and initial scaling of grip force responses, afferents from intrinsic and extrinsic hand muscles and interphalangeal joints do not respond to load increases early enough to allow them to contribute to the initiation of these grip responses. The muscle afferents respond reliably after the onset of the reactive grip force response and their discharge rates are related to changes in force output and, hence, to muscle activity (Fig. 2C). Thus, these muscle afferents are primarily concerned with events in the muscle itself rather than functioning as exteroceptors sensing mechanical events at the fingertips.

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