We thank Mr. T. Nishida (Technician, Dept of Sales, Division of Device Performance Materials, Nitta Co., Ltd, Osaka, Japan.) for technical support.

The series of studies in the present paper were approved by Gunma University Ethical Review Board for Medical Research Involving Human Subjects.
NOTE: Inclusion criteria for participants were the ability to understand the use of minimal force and the ability to perform the task with the thumb and index finger. Exclusion criteria were selected based on the purpose of the experiments.
1. Equipment preparation
<ol>
	<li>Connect two sensor connector cables to the USB ports of a computer. Pull up the lever attached to the sensor connector and insert the sensor&#8217;s tab into the insertion slot. Return the attached lever to its original position.</li>
	<li>Open the sensor software on a computer. Make sure that real-time pressure distribution maps appear automatically on the monitor when the sensor sheets are correctly connected.</li>
	<li>Pressure adjustment
	<ol>
		<li>Insert the sensing area of the sensor sheet one by one into a compressor rig.</li>
		<li>Turn on the air valve of the compressor&#8217;s controller and start to apply pressure. Operate the regulator and adjust to the appropriate load value (i.e., 172 kPa) to check the indicator on the controller. Make sure that the whole area of the sensor sheet is equally pressurized on the monitor.</li>
	</ol>
	</li>
	<li>While applying pressure to the sensor sheets, perform equilibration and calibration. 
	NOTE: Equilibration is an operation to adjust the reactivity of the sensor cells equally. Calibration is an operation to convert the pressure on the sensor sheet (raw sum) into a unit of weight (grams or Newtons) and display it. Both must be done for the sensor sheet before starting data collection for each participant.
	<ol>
		<li>Select Tools | Equilibration on the software main window. Click Equilibrate-1 | Start in the equilibration dialog box. Check the equilibration result in the dialog box and confirm the window of equilibration changes color to gray.</li>
		<li>Save the equilibration settings by clicking Save Eq. File in the equilibration dialog box. Enter the equilibration file name and click Save in the Save As dialog box.</li>
		<li>Next, perform calibration by selecting Tools | Calibration. Click the Add and enter the load value (134.33 N) in the Applied Force box.</li>
		<li>Click the Start button in the dialog box. Check the calibration result in the calibration dialog box and confirm that the calibration was done correctly; the value of Newton is shown as 134.33 and the value of loaded Cells matches with that of the sensor sheets being used if the calibration was done correctly.</li>
		<li>After that, save the calibration setting by clicking Save Cal. File. Enter the calibration file name and click Save in the Save As dialog box. After the equilibration and calibration, turn off the air valve on the controller and extract the sensor sheet from the compressor.</li>
	</ol>
	</li>
</ol>
2. Measurement
<ol>
	<li>Preparation
	<ol>
		<li>Connect each device and start up the software according to steps 1.1. and 1.2. Make sure that two real-time pressure distribution maps for each sensor sheet are displayed when the sensor sheets are connected via the cable at the same time. 
		NOTE: In this experiment, two sensor sheets are needed to measure the thumb and index finger, respectively. It is necessary to perform equilibration and calibration for each of them according to the procedures described in section 1.4.</li>
		<li>Recall the equilibration and calibration files created in steps 1.4.2. and 1.4.5. With the real-time pressure distribution map active, select Tools | Load Equilibration File. Select the equilibration file and click Open. Then, select Tools | Load Calibration File. Select the calibration file and click Open. Make sure that the real-time pressure distribution map is displayed in Newtons after loading calibration file. Perform the above for each of the two maps.</li>
		<li>Attach the pressure-sensitive parts of the two sensor sheets to both sides of the iron cube using double-sided tape. To prevent the sensor sheets from being damaged, cut 3&#8722;5 mm lengths of tape and place them on the four corners on the outside of the iron cube. Make sure that the surface of the sensor sheet is on the outside.</li>
		<li>Place the iron cube on top of a setting stand on a table before the measurement.</li>
		<li>After arranging the measurement environment, fix the recording settings for the movie frames, period, and frequency. Select the Options | Acquisition Parameter command. In the data acquisition parameter dialog box, enter 36000 in the movie frames, 0.01 in the Period, and 100 in the frequency. Click OK and close the dialog box.</li>
	</ol>
	</li>
	<li>Starting the measurement 
	NOTE: Figure 1 demonstrates a grip and lift task.
	<ol>
		<li>Have the participant sit in front of a table and adjust the table height (participant&#8217;s shoulder joint flexion 0&#176; and elbow joint flexion 90&#176; position). Set the iron cube and setting stand 30 cm from the participant in the midsagittal plane on the table. Wipe the participant&#8217;s finger pulps with an alcohol swab or towelette.</li>
		<li>Give the participant verbal instructions as follows: &#8220;Use minimal force with your thumb and index finger to grasp both sides of the iron cube to which the sensor sheets are attached. After that, lift it approximately 5 cm above the setting stand, hold it for 5&#8722;7 s, and then place it back on the setting stand.&#8221;</li>
		<li>If the participant is ready, give them a cue to start the task and start a recording by clicking Record on the toolbar. Click Center Of Force Trajectory to monitor the COP while recording. When the task is over, click Stop on the toolbar. After the recording, save the movie data by selecting File | Save Movie as. Enter the movie file name and click Save in the dialog box. 
		NOTE: The weight of the iron cube, number of lifts, and the interval between tasks should be considered according to the purpose of the experiment and task difficulty.</li>
	</ol>
	</li>
	<li>Change the measurement conditions according to the purpose of the experiment. For example, to investigate the effect of dual task interference in a grip and lift task, adjust the measurement conditions as follows depending on the type of interference.
	<ol>
		<li>For postural interference, have the participant stand in front of a table and adjust the table height. Give the participant verbal instructions as follows: &#8220;Stand on one leg, and use minimal force with your thumb and index finger to lift the iron cube approximately 5 cm above the setting stand. Hold it for 5&#8722;7 s and then place it back on the setting stand.&#8221;</li>
		<li>For visual interference, have the participant sit in front of a table and adjust the table height. Give the participant verbal instructions as follows: &#8220;Close your eyes. Use minimal force with your thumb and index finger with to lift the iron cube approximately 5 cm above the setting stand. Hold it for 5&#8722;7 s and place it back on the setting stand.&#8221; Allow participants to touch the sensors without exceeding 0.5 N before closing their eyes.</li>
		<li>For cognitive interference, have the participant sit in front of a table and adjust the table height. Give the participant verbal instructions as follows: &#8220;As a calculation task, continuously subtract 7 from 100 as accurately as possible. While performing the calculation, use minimal force with your thumb and index finger to lift the iron cube approximately 5 cm above the setting stand. Hold it for 5&#8722;7 s and place it back on the setting stand.&#8221;</li>
		<li>For contralateral hand movement interference (Figure 2), have the participant sit in front of a table and adjust the table height. Place the peg board 30 cm from the participant in the midsagittal plane next to the iron cube and consider the size and number of pegs to adjust the task difficulty. Give the participant verbal instructions as follows: &#8220;Manipulate the iron cube with minimal force using your thumb and index finger. Lift and hold the iron cube approximately 5 cm above the setting stand with one hand, and invert the peg using the other hand. Repeat using the opposite hand.&#8221;</li>
	</ol>
	</li>
</ol>
3. Data analysis
<ol>
	<li>Analysis of grip force
	<ol>
		<li>Start the software on the computer. Click File | Open Movie, select the movie file for analysis and Open.</li>
		<li>As the recorded pressure distribution map appears, click Multiple Window View on the map and refer the graph 1 window. Find the point in time which the load (grip force) starts to be applied in each lift, and note the time with reference to this graph.</li>
		<li>After that, save the grip force data in ASCII format. Select File | Save ASCII after making the graph 1 window activated. In the object-graph 1 dialog box, select Panes with the file name and click Save ASCII. In the dialog box, select Save Force, Pressure, and Area values. Specify Force in the Y-axis box, Time in the X-axis box, and Absolute in the Y-mode. Click OK in the property dialog box. Enter the ASCII file name and click Save in the dialog box.</li>
		<li>If information on the contact areas between finger pulps and sensor sheets is needed, specify Contact Area in the Y-axis box and click OK. Enter the ASCII file name and click Save in the dialog box.</li>
		<li>Next, open the movie file. Confirm that the file is opened in spreadsheet format and Frames, Time, Absolute time, Raw Sum and Force are noted. With reference to the time noted in step 3.1.2., find a cell which the load starts to be applied; the load values starts to increase and exceed 0.5N in the force row.</li>
		<li>Calculate the total grip force used in a range, which is the sum of the values from the cell was applied in the force line.</li>
	</ol>
	</li>
	<li>Analysis of center of pressure
	<ol>
		<li>Start the software. Click File | Open Movie, select the movie file for analysis and click Open.</li>
		<li>With the pressure distribution map active, click Play Forward to play the movie. Make sure that the COP trajectory appears on the pressure distribution map. Find the frame which the COP starts to appear in each lift with Next Frame or Previous Frame, which are the commands to move forward or backward the frames. Then, note that frame number.</li>
		<li>After that, save the COP data in ASCII format. Select File | Save ASCII with the distribution map active. Specify Center of Force in the data type dialog box and Whole movie in the movie range dialog box. Click OK in the property dialog box. Enter the ASCII file name and click Save in the dialog box.</li>
		<li>Next, open the movie file. Confirm that the file opens in spreadsheet format and COMMENTS Frame, Time, Absolute time, Row, Col and Raw Sum are noted. With reference to the frame noted in steps 3.2.2., find a cell (1) which the COP starts to appear.</li>
		<li>Calculate the COP trajectory length between frames. Select a cell (2) after the row including the frame which the COP starts to appear. Insert the following calculation formula: (=SQRT((Row cell (2) -Row cell (1))^2+(Col cell (2) -Col cell (1))^2). The sum of the COP trajectory length between frames in a range is the total COP trajectory within that range. 
		NOTE:&#160;In the graph 1 window, the vertical line shows the load value (N), and the horizontal line shows the time (s). This load value corresponds to the grip force. Data saved in ASCII format can be used in applications such as spreadsheets and text editors. In this experiment, the participants were instructed to hold the cube for 5&#8722;7 s in the task, so the grip force and COP trajectory were calculated and recorded for 4 s from their first appearance. In the spread sheet of the COP data, the position of the COP on X- and Y-axis coordinates is shown as a value.</li>
	</ol>
	</li>
</ol>

<ol><li>Johansson, R. S., Flanagan, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Coding+and+use+of+tactile+signals+from+the+fingertips+in+object+manipulation+tasks%5BTitle%5D)+AND+%22Nature+Reviews+Neuroscience%22%5BJournal%5D)">Coding and use of tactile signals from the fingertips in object manipulation tasks.</a> Nature Reviews Neuroscience. 10 (5), 345-359 (2009).</li>
<li>Cole, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Grasp+force+control+in+older+adults%5BTitle%5D)+AND+%22Journal+of+Motor+Behavior%22%5BJournal%5D)">Grasp force control in older adults.</a> Journal of Motor Behavior. 23 (4), 251-258 (1991).</li>
<li>Lang, C. E., Schieber, M. H. Stroke. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aLang%2C+CE+%22Sensorimotor+control+of+grasping%22">Sensorimotor control of grasping</a>. Nowak, D. A., Hermsdörfer, J. , Cambridge University Press. New York, NY. 296-310 (2009).</li>
<li>Johansson, R. S., Westling, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Roles+of+glabrous+skin+receptors+and+sensorimotor+memory+in+automatic+control+of+precision+grip+when+lifting+rougher+or+more+slippery+objects%5BTitle%5D)+AND+%22Experimental+Brain+Research%22%5BJournal%5D)">Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects.</a> Experimental Brain Research. 56 (3), 550-564 (1984).</li>
<li>Parikh, P. J., Cole, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Handling+objects+in+old+age%3A+forces+and+moments+acting+on+the+object%5BTitle%5D)+AND+%22Journal+of+Applied+Physiology%22%5BJournal%5D)">Handling objects in old age: forces and moments acting on the object.</a> Journal of Applied Physiology. 112 (7), 1095-1104 (2012).</li>
<li>Augurelle, A. S., Smith, A. M., Lejeune, T., Thonnard, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Importance+of+cutaneous+feedback+in+maintaining+a+secure+grip+during+manipulation+of+hand-held+objects%5BTitle%5D)+AND+%22Journal+of+Neurophysiology%22%5BJournal%5D)">Importance of cutaneous feedback in maintaining a secure grip during manipulation of hand-held objects.</a> Journal of Neurophysiology. 89 (2), 665-671 (2003).</li>
<li>Monzée, J., Lamarre, Y., Smith, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+effects+of+digital+anesthesia+on+force+control+using+a+precision+grip%5BTitle%5D)+AND+%22Journal+of+Neurophysiology%22%5BJournal%5D)">The effects of digital anesthesia on force control using a precision grip.</a> Journal of Neurophysiology. 89 (2), 672-683 (2003).</li>
<li>Fortier-Poisson, P., Langlais, J. S., Smith, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Correlation+of+fingertip+shear+force+direction+with+somatosensory+cortical+activity+in+monkey%5BTitle%5D)+AND+%22Journal+of+Neurophysiology%22%5BJournal%5D)">Correlation of fingertip shear force direction with somatosensory cortical activity in monkey.</a> Journal of Neurophysiology. 115 (1), 100-111 (2016).</li>
<li>Kurihara, J., Lee, B., Hara, D., Noguchi, N., Yamazaki, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Increased+center+of+pressure+trajectory+of+the+finger+during+precision+grip+task+in+stroke+patients%5BTitle%5D)+AND+%22Experimental+Brain+Research%22%5BJournal%5D)">Increased center of pressure trajectory of the finger during precision grip task in stroke patients.</a> Experimental Brain Research. 237 (2), 327-333 (2018).</li>
<li>Noguchi, N., et al. Grip force control during object manipulation in cervical myelopathy. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aNoguchi%2C+N+%22Spinal+Cord%22">Spinal Cord</a>. , (2020).</li>
<li>Lee, B., Miyanjo, R., Tozato, F., Shiihara, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Dual-task+interference+in+a+grip+and+lift+task%5BTitle%5D)+AND+%22The+Kitakanto+Medical+Journal%22%5BJournal%5D)">Dual-task interference in a grip and lift task.</a> The Kitakanto Medical Journal. 64 (4), 309-312 (2014).</li>
</ol>

The authors declare that they have no competing financial interests.

This experimental procedure provides evidence that a flexible pressure sensor sheet could be useful for evaluating spatial stability during precision grip. Altered grip force direction represents grasping spatial instability such as a finger slip. However, existing load cell-type force direction instruments have a limitation in terms of ensuring a natural reach-to-grip movement. To resolve this technical problem, the COP trajectory of the area between the finger pulps and contact surface based on a biomechanical relationship was monitored. The results suggest that the COP displacement is caused by deviated&#160;force direction. Thus, the study found that the COP trajectory length is a useful kinetic parameter for evaluating the spatial stability in a precision grip.
A critical factor influencing the outcome of the experiment was each participant&#8217;s understanding of the experimental protocol. If participants did not understand the aim of the experiment, they tended to use a relatively large GF in order to avoid spatial instability. Intentionally exaggerated GF interferes with the evaluation of precision grip. Another factor influencing the outcome can be the area between the fingertip and contact surface of the object. If the fingertip is not properly in contact with the surface of the object, the COP is not estimated appropriately. During practical trials, the examiner must adjust the location and orientation of the cube. When the cube is not placed properly, the fingertip protrudes from the edge of the cube, or participants tend to increase trunk and shoulder movements to compensate for hand orientation for grasping.
One limitation of the protocol is the unclear biomechanics of the COP. A slip, roll, or twist between the finger pulps and contact area can account for COP displacement, resulting in spatial instability. This is because the COP is calculated in the X- and Y- axes. Moreover, it is technically difficult to link the two COPs of the thumb and index fingers. Although there are limitations, it is clear that there are benefits to evaluating the spatial stability of grasping using the COP trajectory.

Force control is the fundamental basis of precision grip. Compared with power grip, precision grip evaluates the minimal force output reflecting the ability to manipulate an object. Multiple sensorimotor systems contribute to precision grip. For example, during a grip and lift task, visual information enables the perception of the object&#8217;s size and shape. After the fingertips touch the object, tactile signals are delivered to the somatosensory cortex to adjust the precision grip force. Grip force (GF) is generated when the fingertips make contact with the object, and it increases during the lifting phase1. When an object approaches the goal height in the air, healthy young adults produce the minimal GF to optimize cutaneous input from the finger pulps and conserve energy. On the other hand, older adults use a large grip force to avoid letting the object slip from their grip2. In stroke patients, onset of grip force is delayed and the ability to adjust the safety margin is impaired due to sensory and motor deficits. Exaggerated grip force is considered to be a strategic response to compensate for sensory and motor deficits3.
The standard protocol to measure GF control in precision grip was suggested by Johansson and Westling in the 1980s4. They developed a device to monitor both load and grip forces simultaneously. Since then, GF amplitude and its temporal regulation have been used as typical kinetic parameters in numerous studies on precision grip. Another kinetic parameter is the force direction5. The force direction results from a combination of grip and lift forces. In order to maintain stable precision grip, properly directed grip and lift forces must be generated between the thumb and index finger, and the deviated force direction can cause spatial instability. Although various load cell-type force direction instruments are used in grasping studies, these instruments have a limitation in terms of monitoring the grip force control in manipulating objects of different sizes and shapes used in daily living. Thus, a flexible and attachable sensor is essential to investigate the relationships between grip force control and daily functions.
The purpose of this protocol is to indirectly evaluate the finger force direction during manipulation of an object based on the biomechanical relationship in which deviated force direction causes Center of Pressure (COP) replacement. The COP is the center of all the forces, and represents how the forces are balanced on the sensor sheet. The use of COP to evaluate grip force control was first suggested by Augurelle et al.6. They monitored COP displacement to investigate the role of cutaneous feedback and found that deviated COP occurred after digital anesthesia. However, COP displacement was monitored only vertically in their study; therefore, the COP displacement in a three-dimensional space has not been adequately evaluated. To solve this limitation a thin, flexible, and high spatial resolution pressure sensor sheet was used to measure COP. Relatively high spatial resolution sensors (~60&#8211;100 points per cm2) to measure grip force control have been used7,8, but recent advances in spatial resolution (248 points per cm2) allow measurement of the COP trajectory as a parameter to quantify spatial stability. This paper describes the experimental procedure and discusses how finger COP contributes to the understanding of the physiology and pathophysiology of grasping.

<table><tbody><tr><td>Alcohol swab</td><td></td><td></td><td>Wipe participant&amp;rsquo;s finger pulps</td></tr><tr><td>Compressor</td><td>Nitta Corporation</td><td></td><td>Apply pressure to the sensor seats</td></tr><tr><td>Computer</td><td></td><td></td><td></td></tr><tr><td>Controller of compressor</td><td>Nitta Corporation</td><td></td><td>Use to manupirate the compressor</td></tr><tr><td>Double-sides tapes</td><td></td><td></td><td>Use to attach the sensorseats to the iron cube</td></tr><tr><td>Iron cube</td><td></td><td></td><td>150-250g, 30&amp;times;30&amp;times;30 mm</td></tr><tr><td>Sensor connector</td><td></td><td></td><td>Connect the sensorseats to computer.</td></tr><tr><td>Sensor sheet</td><td></td><td></td><td>Pressure Mapping Sensor 5027, Tekscan, South Boston, MA, 50 USA</td></tr><tr><td>Setting stand</td><td></td><td></td><td>Set the iron cube on it during the measurement</td></tr><tr><td>Software; I-SCAN 5027, Ver. 7.51</td><td>Nitta Corporation</td><td></td><td></td></tr><tr><td>Table</td><td></td><td></td><td>Use for the measurement</td></tr></tbody></table>

measurement of spatial stability in precision grip

The purpose of the protocol is to indirectly evaluate the direction of the finger force during manipulation of a handheld object based on the biomechanical relationships in which deviated force direction causes center of pressure (COP) replacement. To evaluate this, a thin, flexible, and high spatial resolution pressure sensor sheet is used. The system allows measurement of the COP trajectory in addition to the force amplitude and its temporal regulation. A series of experiments found that increased trajectory length reflected a sensorimotor deficit in stroke patients, and that decreased COP trajectory reflects a compensatory strategy to avoid an object slipping from the hand grip in the elderly. Moreover, the COP trajectory could also be decreased by dual task interference. This article describes the experimental procedure and discusses how finger COP contributes to an understanding of the physiology and pathophysiology of grasping.

Several studies have introduced experimental protocols and two kinetic parameters (the COP trajectory and the GF) to measure finger force during manipulation of an object. In previous studies, it was found that the COP trajectory increased in stroke patients9. In cervical myelopathy patients, the GF correlated with the cutaneous pressure threshold and upper extremity function10. In healthy young subjects, the GF increased with cognitive interference11. Similar exaggerated GF was found in contralateral hand movement interference. Figure 3 shows the COP trajectories and the GF traces of the dominant index finger in single and dual tasks for representative young and elderly adults. The GF increased in the contralateral hand movement interference. In contrast, the COP trajectories tended to decrease (unpublished data).
Kurihara et al.9 investigated the grip force coordination of grasping in stroke patients. They found that the COP trajectory increased in the paretic hand, although the GFs were not significantly different from the nonparetic hand. Hemorrhagic patients showed longer COP trajectories of the thumb and index finger compared to those in ischemic patients. They also found that the kinetic parameters were correlated with not only somatosensory function, but also cognitive function.
In cervical myelopathy patients, Noguchi et al.10 evaluated the kinetic characteristics of individual finger grip force and investigated the relationship between the grip force and upper extremity function. They found that the GF was associated with the severity of hand dysfunction. Although there was no significant correlation in pinch power or grip power, there was a positive correlation between the GF and the cutaneous pressure threshold.
Lee et al.11 investigated dual task interference in a grip and lift task. They reported that the GF increased in both hands mainly due the dual cognitive task. They also found a correlation between the perceived difficulty and maximum grip force in the dominant hand.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59699/59699fig01.jpg" /> 
Figure 1: Grip and lift task.&#160;Participants gripped the cube using the thumb and index finger, lifted it approximately 5 cm, and held it for 5&#8722;7 s. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59699/59699fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59699/59699fig02.jpg" /> 
Figure 2: Dual task interference with contralateral hand movement.&#160;Participants performed a grip and lift task with one hand and simultaneously conducted a peg test with the other. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59699/59699fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59699/59699fig03.jpg" /> 
Figure 3: COP trajectories and the GF traces of the dominant index finger in single and dual tasks for representative young and elderly adults. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59699/59699fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Measurement of Spatial Stability in Precision Grip at JoVE.com

Measurement of Spatial Stability in Precision Grip

The goal of this protocol is to measure the center of pressure (COP) replacement using a high spatial resolution sensor sheet to reflect the spatial stability in a precision grip. The use of this protocol could contribute to greater understanding of the physiology and pathophysiology of grasping.

The purpose of the protocol is to indirectly evaluate the direction of the finger force during manipulation of a handheld object based on the ...

measurement-of-spatial-stability-in-precision-grip

Nanyang Technological University

Research

JoVE Journal

Behavior

3.1K Views.  Geriatrics Research Institute and Hospital. Om een uitgebreid inzicht in de Grip Force controle van het grijpen te verkrijgen, is het belangrijk om een vinger kracht richting te evalueren. We stellen een nieuwe eenvoudigere techniek voor voor het meten van ruimtelijke stabiliteit in precisiegreep, om de richting van de vingerkracht in een klinische omgeving te evalueren. Het aantonen van de procedure, zal Ryoto Teshima, een promovendus uit ons laboratorium.Voordat u een analyse start, sluit u twee sensorconnectorkabels aan op de...

Video: Measurement of Spatial Stability in Precision Grip

Measuring Motor Coordination in Mice

Mice are increasingly being used in behavioral neuroscience, largely replacing rats as the behaviorist's animal of choice. Before aspects of behavior such as emotionality or cognition can be assessed, however, it is vital to determine whether the motor capabilities of e.g. a mutant or lesioned mouse allow such an assessment. Performance on a maze task requiring strength and coordination, such as the Morris water maze, might well be impaired in a mouse by motor, rather than cognitive, impairments, so it is essential to selectively dissect the latter from the former. For example, sensorimotor impairments caused by NMDA antagonists have been shown to impair water maze performance2. 
Motor coordination has traditionally been assessed in mice and rats by the rotarod test, in which the animal is placed on a horizontal rod that rotates about its long axis; the animal must walk forwards to remain upright and not fall off. Both set speed and accelerating versions of the rotarod are available.
The other three tests described in this article (horizontal bar, static rods and parallel bars) all measure coordination on static apparatus. The horizontal bar also requires strength for adequate performance, particularly of the forelimbs as the mouse initially grips the bar just with the front paws. 
Adult rats do not perform well on tests such as the static rods and parallel bars (personal observations); they appear less well coordinated than mice. I have only tested male rats, however, and male mice seem generally less well coordinated than females. Mice appear to have a higher strength:weight ratio than rats; the Latin name, Mus musculus, seems entirely appropriate. The rotarod, the variations of the foot fault test12 or the Catwalk (Noldus)15 apparatus are generally used to assess motor coordination in rats.

Protocols are presented for two established motor coordination tasks, the accelerating rotarod and horizontal bar, also two tests developed in Oxford recently, the static rods and parallel bars. These tests can detect motor impairments potentially of interest in their own right, as well as being possible variables in tests of other areas of behavior.

Mice are increasingly being used in behavioral neuroscience, largely replacing rats as the behaviorist's animal of choice. Before aspects of behavior such ...

Neuroscience

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Proprioceptive drift, which is a perceptual shift in body-part position from the unseen real body to a visible body-like image, has been measured as the behavioral correlate for the sense of ownership. Previously, the estimation of proprioceptive drift was limited to one spatial dimension, such as height, width, or depth. As the hand can move freely in 3D, measuring proprioceptive drift in only one dimension is not sufficient for the estimation of the drift in real life situations. In this article, we provide a novel method to estimate proprioceptive drift on a 2D plane using the mirror illusion by combining an objective behavioral measurement (hand position tracking) and subjective, phenomenological assessment (subjective assessment of hand position and questionnaire) with a sophisticated machine learning approach. This technique permits not only an investigation of the underlying mechanisms of the sense of ownership and agency but also assists in the rehabilitation of a missing or paralyzed limb and in the design rules of real-time control systems with a self-body-like usability, in which the operator controls the system as if it were part of his/her own body.

This article describes a novel method to estimate proprioceptive drift on a 2D plane using the mirror illusion and combining a psychophysical procedure with an analysis using machine learning.

Proprioceptive drift, which is a perceptual shift in body-part position from the unseen real body to a visible body-like image, has been measured as the ...

Behavioral Assessment of Manual Dexterity in Non-Human Primates

The corticospinal (CS) tract is the anatomical support of the exquisite motor ability to skillfully manipulate small objects, a prerogative mainly of primates1. In case of lesion affecting the CS projection system at its origin (lesion of motor cortical areas) or along its trajectory (cervical cord lesion), there is a dramatic loss of manual dexterity (hand paralysis), as seen in some tetraplegic or hemiplegic patients. Although there is some spontaneous functional recovery after such lesion, it remains very limited in the adult. Various therapeutic strategies are presently proposed (e.g. cell therapy, neutralization of inhibitory axonal growth molecules, application of growth factors, etc), which are mostly developed in rodents. However, before clinical application, it is often recommended to test the feasibility, efficacy, and security of the treatment in non-human primates. This is especially true when the goal is to restore manual dexterity after a lesion of the central nervous system, as the organization of the motor system of rodents is different from that of primates1,2. Macaque monkeys are illustrated here as a suitable behavioral model to quantify manual dexterity in primates, to reflect the deficits resulting from lesion of the motor cortex or cervical cord for instance, measure the extent of spontaneous functional recovery and, when a treatment is applied, evaluate how much it can enhance the functional recovery.
The behavioral assessment of manual dexterity is based on four distinct, complementary, reach and grasp manual tasks (use of precision grip to grasp pellets), requiring an initial training of adult macaque monkeys. The preparation of the animals is demonstrated, as well as the positioning with respect to the behavioral set-up. The performance of a typical monkey is illustrated for each task. The collection and analysis of relevant parameters reflecting precise hand manipulation, as well as the control of force, are explained and demonstrated with representative results. These data are placed then in a broader context, showing how the behavioral data can be exploited to investigate the impact of a spinal cord lesion or of a lesion of the motor cortex and to what extent a treatment may enhance the spontaneous functional recovery, by comparing different groups of monkeys (treated versus sham treated for instance). Advantages and limitations of the behavioral tests are discussed. The present behavioral approach is in line with previous reports emphasizing the pertinence of the non-human primate model in the context of nervous system diseases2,3.

As manual dexterity is a prerogative mainly of primates, behavioral tasks have been developed in macaque monkeys. Four reach and grasp prehension tasks, measuring hand manipulation ability and force, allow to establish functional recovery after a lesion of the central nervous system and to test the effect of a treatment.

The corticospinal (CS) tract is the anatomical support of the exquisite motor ability to skillfully manipulate small objects, a prerogative mainly of ...

Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans

Prehension, the act of reaching to grasp an object, is central to the human experience. We use it to feed ourselves, groom ourselves, and manipulate objects and tools in our environment. Such behaviors are impaired by many sensorimotor disorders, yet our current understanding of their neural control is far from complete. Current technologies for investigating human reach-to-grasp movements often utilize motion tracking systems that can be expensive, require the attachment of markers or sensors to the hands, impede natural movement and sensory feedback, and provide kinematic output that can be difficult to interpret. While generally effective for studying the stereotypical reach-to-grasp movements of healthy sighted adults, many of these technologies face additional limitations when attempting to study the unpredictable and idiosyncratic reach-to-grasp movements of young infants, unsighted adults, and patients with neurological disorders. Thus, we present a novel, inexpensive, and highly reliable yet flexible protocol for quantifying the temporal and kinematic structure of idiosyncratic reach-to-grasp movements in humans. High speed video cameras capture multiple views of the reach-to-grasp movement. Frame-by-frame video analysis is then used to document the timing and magnitude of pre-defined behavioral events such as movement start, collection, maximum height, peak aperture, first contact, and final grasp. The temporal structure of the movement is reconstructed by documenting the relative frame number of each event while the kinematic structure of the hand is quantified using the ruler or measure function in photo editing software to calibrate 2 dimensional linear distances between two body parts or between a body part and the target. Frame-by-frame video analysis can provide a quantitative and comprehensive description of idiosyncratic reach-to-grasp movements and will enable researchers to expand their area of investigation to include a greater range of naturalistic prehensile behaviors, guided by a wider variety of sensory modalities, in both healthy and clinical populations.

This protocol describes how to use frame-by-frame video analysis to quantify idiosyncratic reach-to-grasp movements in humans. A comparative analysis of reaching in sighted versus unsighted healthy adults is used to demonstrate the technique, but the method can also be applied to the study of developmental and clinical populations.

Prehension, the act of reaching to grasp an object, is central to the human experience. We use it to feed ourselves, groom ourselves, and manipulate ...

A Vibrotactile Feedback Device for Seated Balance Assessment and Training

Postural perturbations, motion tracking, and sensory feedback are modern techniques used to challenge, assess, and train upright sitting, respectively. The goal of the developed protocol is to construct and operate a sitting platform that can be passively destabilized while an inertial measurement unit quantifies its motion and vibrating elements deliver tactile feedback to the user. Interchangeable seat attachments alter the stability level of the device to safely challenge sitting balance. A built-in microcontroller allows fine-tuning of the feedback parameters to augment sensory function. Posturographic measures, typical of balance assessment protocols, summarize the motion signals acquired during timed balance trials. No dynamic sitting protocol to date provides variable challenge, quantification, and sensory feedback free of laboratory constraints. Our results demonstrate that non-disabled users of the device exhibit significant changes in posturographic measures when balance difficulty is altered or vibrational feedback provided. The portable, versatile device has potential applications in rehabilitation (following skeletal, muscular, or neurological injury), training (for sports or spatial awareness), entertainment (via virtual or augmented reality), and research (of sitting-related disorders).

A sitting platform has been developed and assembled that passively destabilizes sitting posture in humans. During the user&#39;s stabilizing task, an inertial measurement unit records the device&#39;s motion, and vibrating elements deliver performance-based feedback to the seat. The portable, versatile device may be used in rehabilitation, assessment, and training paradigms.

Postural perturbations, motion tracking, and sensory feedback are modern techniques used to challenge, assess, and train upright sitting, respectively. ...

Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication

Computerized dynamic posturography with the EquiTest is an objective technique for measuring postural strategies under challenging static and dynamic conditions. As part of a diagnostic assessment, the early detection of postural deficits is important so that appropriate and targeted interventions can be prescribed. The Sensory Organization Test (SOT) on the EquiTest determines an individual&#39;s use of the sensory systems (somatosensory, visual, and vestibular) that are responsible for postural control. Somatosensory and visual input are altered by the calibrated sway-referenced support surface and visual surround, which move in the anterior-posterior direction in response to the individual&#39;s postural sway. This creates a conflicting sensory experience. The Motor Control Test (MCT) challenges postural control by creating unexpected postural disturbances in the form of backwards and forwards translations. The translations are graded in magnitude and the time to recover from the perturbation is computed.
Intermittent claudication, the most common symptom of peripheral arterial disease, is characterized by a cramping pain in the lower limbs and caused by muscle ischemia secondary to reduced blood flow to working muscles during physical exertion. Claudicants often display poor balance, making them susceptible to falls and activity avoidance. The Ankle Brachial Pressure Index (ABPI) is a noninvasive method for indicating the presence of peripheral arterial disease and intermittent claudication, a common symptom in the lower extremities. ABPI is measured as the highest systolic pressure from either the dorsalis pedis or posterior tibial artery divided by the highest brachial artery systolic pressure from either arm. This paper will focus on the use of computerized dynamic posturography in the assessment of balance in claudicants.

Individuals with intermittent claudication exhibit poor balance compared to healthy controls. Computerized dynamic posturography is an objective method for measuring an individual's postural responses to balance disturbances. This provides an objective reflection of the person&#x2019;s ability to respond to situations under which sensory stimuli are altered and unexpected perturbations occur.

Computerized dynamic posturography with the EquiTest is an objective technique for measuring postural strategies under challenging static and dynamic ...

Medicine

A Standardized Method for Measurement of Elbow Kinesthesia

Proprioception is an important component of controlled movement. The threshold to detection of passive movement (TDPM) is a commonly used method for quantifying the proprioceptive submodality of kinesthesia in research settings. The TDPM paradigm has been found to be valid and reliable; however, the equipment and methods used for TDPM vary between studies. In particular, the research laboratory apparatuses for producing passive movement of an extremity are often custom designed by individual laboratories or inaccessible due to high cost. There is a need for a standardized, valid, and reliable method for measuring TDPM using readily available equipment. The purpose of this protocol is to provide a standardized method for measurement of TDPM at the elbow that is economical, easy to administer, and that produces quantitative results for measurement purposes in research-based settings. This method was tested on 20 healthy adults without neurological impairment, and eight adults with chronic stroke. The results obtained suggest this method is a reliable way to quantify elbow TDPM in healthy adults, and provides initial support for validity. Researchers seeking a balance between equipment affordability and measurement precision are most likely to find this protocol of benefit.

Here, we present a standardized method for measurement of elbow passive kinesthesia using the threshold to detection of passive movement (TDPM) that is appropriate for a research setting.

Proprioception is an important component of controlled movement. The threshold to detection of passive movement (TDPM) is a commonly used method for ...

Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact

The measurement of dynamic scapular kinematics is complex due to the sliding nature of the scapula beneath the skin surface. The aim of the study was to clearly describe the acromion marker cluster (AMC) method of determining scapular kinematics when using a passive marker motion capture system, with consideration for the sources of error which could affect the validity and reliability of measurements. The AMC method involves placing a cluster of markers over the posterior acromion, and through calibration of anatomical landmarks with respect to the marker cluster it is possible to obtain valid measurements of scapular kinematics. The reliability of the method was examined between two days in a group of 15 healthy individuals (aged 19-38 years, eight males) as they performed arm elevation, to 120&#176;, and lowering in the frontal, scapular and sagittal planes. Results showed that between-day reliability was good for upward scapular rotation (Coefficient of Multiple Correlation; CMC = 0.92) and posterior tilt (CMC = 0.70) but fair for internal rotation (CMC = 0.53) during the arm elevation phase. The waveform error was lower for upward rotation (2.7&#176; to 4.4&#176;) and posterior tilt (1.3&#176; to 2.8&#176;), compared to internal rotation (5.4&#176; to 7.3&#176;). The reliability during the lowering phase was comparable to results observed during the elevation phase. If the protocol outlined in this study is adhered to, the AMC provides a reliable measurement of upward rotation and posterior tilt during the elevation and lowering phases of arm movement.

This report presents details of how to adopt the acromion marker cluster method of obtaining scapular kinematics when using a passive marker motion capture device. As has been described in the literature, this method provides a robust, non-invasive, three-dimensional, dynamic and valid measurement of scapular kinematics, minimizing skin movement artifact.

The measurement of dynamic scapular kinematics is complex due to the sliding nature of the scapula beneath the skin surface. The aim of the study was to ...

Measurement of the Hand Transmitted Vibration of the Human Hand Arm System During Operation of a Hand Tractor

Operators of hand tractors are exposed to high levels of hand transmitted vibration (HTV). This vibration, which can be both irksome and hazardous to human health, is imparted to the operator via his or her hands and arms. However, a standardized method for measuring HTV of hand tractors has yet to be defined. The aim of the study was to present an experimental method for the investigation of the biodynamic response and vibration transmissibility of the hand-arm system during the operation of a hand tractor in a stationary mode. Measurements were performed with ten subjects using three grip forces and three handle vibration levels to examine the influences of the hand pressure and frequency on hand transmitted vibration (HTV). The results indicate that the tightness of grip on the handle influences the vibration response of the hand-arm system, especially at frequencies between 20 and 100 Hz. The transmission of lower frequencies in the hand-arm system was relatively unattenuated. In comparison, attenuation was found to be quite marked for higher frequencies during the operation of the hand tractor. The vibration transmissibility to different parts of the hand-arm system decreased with the increase of the distance from the vibration source. The proposed methodology contributes to the collection of consistent data for the evaluation of operator vibration exposure and the ergonomics development of hand tractors.

Here, we present a standardized method for measurement of the hand transmitted vibration from handles of a single-axle tractor with special reference to changes in grip force and vibration frequency.

Operators of hand tractors are exposed to high levels of hand transmitted vibration (HTV). This vibration, which can be both irksome and hazardous to ...

Engineering

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

To grasp an object successfully, we must select appropriate contact regions for our hands on the surface of the object. However, identifying such regions is challenging. This paper describes a workflow to estimate the contact regions from marker-based tracking data. Participants grasp real objects, while we track the 3D position of both the objects and the hand, including the fingers' joints. We first determine the joint Euler angles from a selection of tracked markers positioned on the back of the hand. Then, we use state-of-the-art hand mesh reconstruction algorithms to generate a mesh model of the participant's hand in the current pose and the 3D position. 
Using objects that were either 3D printed or 3D scanned-and are, thus, available as both real objects and mesh data-allows the hand and object meshes to be co-registered. In turn, this allows the estimation of approximate contact regions by calculating the intersections between the hand mesh and the co-registered 3D object mesh. The method may be used to estimate where and how humans grasp objects under a variety of conditions. Therefore, the method could be of interest to researchers studying visual and haptic perception, motor control, human-computer interaction in virtual and augmented reality, and robotics.

When we grasp an object, multiple regions of the fingers and hand typically make contact with the object's surface. Reconstructing such contact regions is challenging. Here, we present a method for approximately estimating the contact regions by combining marker-based motion capture with existing deep learning-based hand mesh reconstruction.

To grasp an object successfully, we must select appropriate contact regions for our hands on the surface of the object. However, identifying such regions ...

Measurement of Spatial Stability in Precision Grip

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