Research Papers

Design and Performance of a Motor-Driven Mechanism to Conduct Experiments With the Human Index Finger

[+] Author and Article Information
Pei-Hsin Kuo

ReNeu Robotics Laboratory,
Mechanical Engineering,
The University of Texas,
Austin, TX 78712
e-mail: peihsin.kuo@utexas.edu

Jerod Hayes

Mechanical Engineering,
University of Maine,
Orono, ME 04469
e-mail: jerod.s.hayes@umit.maine.edu

Ashish D. Deshpande

ReNeu Robotics Laboratory,
Mechanical Engineering,
The University of Texas,
Austin, TX 78712
e-mail: ashish@austin.utexas.edu

1Corresponding author.

Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANISMS AND ROBOTICS. Manuscript received November 28, 2013; final manuscript received September 8, 2014; published online December 4, 2014. Assoc. Editor: Philippe Wenger.

J. Mechanisms Robotics 7(3), 031010 (Aug 01, 2015) (10 pages) Paper No: JMR-13-1241; doi: 10.1115/1.4028639 History: Received November 28, 2013; Revised September 08, 2014; Online December 04, 2014

Passive properties of the human hands, defined by the joint stiffness and damping, play an important role in hand biomechanics and neuromuscular control. Introduction of mechanical element that generates humanlike passive properties in a robotic form may lead to improved grasping and manipulation abilities of the next generation of robotic hands. This paper presents a novel mechanism, which is designed to conduct experiments with the human subjects in order to develop mathematical models of the passive properties at the metacarpophalangeal (MCP) joint. We designed a motor-driven system that integrates with a noninvasive and infrared motion capture system, and can control and record the MCP joint angle, angular velocity, and passive forces of the MCP joint in the index finger. A total of 19 subjects participated in the experiments. The modular and adjustable design was suitable for variant sizes of the human hands. Sample results of the viscoelastic moment, hysteresis loop, and complex module are presented in the paper. We also carried out an error analysis and a statistical test to validate the reliability and repeatability of the mechanism. The results show that the mechanism can precisely collect kinematic and kinetic data during static and dynamic tests, thus allowing us to further understand the insights of passive properties of the human hand joints. The viscoelastic behavior of the MCP joint showed a nonlinear dependency on the frequency. It implies that the elastic and viscous component of the hand joint coordinate to adapt to the external loading based on the applied frequency. The findings derived from the experiments with the mechanism can provide important guidelines for design of humanlike compliance of the robotic hands.

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Fig. 1

Figure shows the orientation and rotation of the MCP joint. Since the focus of the current work is on motion of the MCP joint, we fixed the PIP and DIP joints. The joint angle was measured from the line joining the wrist and MCP joints, and we defined flexion as positive and extension as a negative rotation. The neutral position of the index finger was defined as the angle at which the MCP joint generated the smallest passive moment in flexion [20].

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Fig. 2

(a) Rest position of the subject's hand and the full setup of the mechanism. First, we attached the markers and surface electromyography (sEMG) sensors on the subject's forearm and aligned the MCP joint with the shaft of the DC motor. Then, we fixed the forearm on the testing panel with the velcro straps and the arm rest, and adjusted the palm holders to fix the hand at the zero position. Finally, we adjusted the driving arm to fit the index finger into the splint. After we secured the subject's hand on the mechanism, we manually moved the driving arm to test the setup. (b) Design of the driving arm and its sub parts. The load cell holder attached on the moment arm (A) can be adjusted with the height (h) and the distance (d) to fit the different hand sizes. The DC motor (B) and the encoder (C) is connected by a chain and sprocket drive. (c) Design of a load cell holder and splint linkage. A piece called the hammer (D) achieves a flush contact between the splint mechanism and the load cell throughout the RoM of the finger. The arrows indicate the sliding direction of the hammer. The hammer and the cylinder have a size tolerance 0.1 mm so that the hammer can slide along the cylinder. The hinge joint in the hammer allows a relative rotation between the hammer and linkage expending out from the holder. The subplot shows a section view of the hammer design. (d) Design of the testing panel and adjustable stand. The palm holders (J) can be moved and fixed to the desired direction and rotate for 360 deg through the two slots on the testing panel. The palm holder can fix the palm in place for all subjects.

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Fig. 3

The diagram shows the signal flow in the mechanism's electronics and computer systems

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Fig. 4

The block diagram of the closed loop of the position control for the motor drive of the mechanism. The motion generator block is achieved with a C++ code which generates desired position of the finger during static test and cyclic motions of the finger at various velocities during the dynamic test.

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Fig. 5

Left plot shows the trajectories of attached markers used to estimate the CoR of the MCP joint. Right plot shows the predicted CoR trajectory of the MCP joint. (a) Phase lag and (b) complex modulus.

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Fig. 6

(a) Peak-to-peak diagram of the joint angle and viscoelastic moment and (b) vector diagram of complex modulus, the storage (Es) and the loss modulus (El), in the relation with the loss angle φ [38]

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Fig. 7

The figure shows the placement of reflective markers and definition of assigned vectors. Four markers T, L, R, and C attached on the load cell holder were used to calculate the vertical vector ¯-8V and horizontal vector ¯-8H to estimate the angle changes between the flushed hammer (D) and the load cell (F) during the dynamic test. The error is defined as the angle variation between the assumed angle of 90 deg and the angle between the two nonzero vectors.

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Fig. 8

An example of errors for one subject in a low speed (a), a higher speed (b), and mean errors from experiments at 14 frequency levels (c)

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Fig. 9

The error bars shows the standard errors of the mean of the passive moments (□) for the repeated measurement in the static test. The Cronbach's alpha coefficient (α) shows that the two repeated measurements have fairly good internal consistencies in the static test (α > 0.7). The figures show the results for six subjects.

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Fig. 10

Variations in the passive moments for six subjects from the static test. Each figure presents mean static passive moments (×) and fitting curves (solid curves) with bounds of the 95% confidence intervals (dashed curves). The vertical line presents the neutral position for each subject [20].

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Fig. 11

Data points inside of the area enclosed by the black dashed lines show the coverage of joint angle and joint velocity data collected from one subject. The blue and green dashed line areas represent the data coverage from the previous studies [23,33].

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Fig. 12

Cyclic motion of the finger driven by the mechanism. The figure shows typical patterns of the joint angle, velocity and viscoelastic moment at a low speed (cyclic frequency = 0.1 Hz, the upper figures) and high speed (cyclic frequency = 0.7 Hz, the bottom figures) for one subject. (a) f = 0.094 Hz, (b) f = 0.19 Hz, (c) f = 0.24 Hz, (d) f = 0.38 Hz, (e) f = 0.44 Hz, (f) f = 0.59 Hz, (g) f = 0.63 Hz, (h) f = 0.72 Hz, and (i) f = 0.76 Hz.

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Fig. 13

A example of the hysteresis loops of τVE − θm plot (mean ± SD) at a range of frequency from 0.094 to 0.76 Hz for one subject. The blue and red color dashed curve demonstrates the loading and unloading average moment at the extension and flexion direction.

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Fig. 14

Mean values of the storage modulus, El, and loss modulus, Es, estimated from the loss angle, φ, with respect to the oscillating frequency




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