HU MAN FACTORS, 1997,39(3),497-506

A Dynamic Mechanical Model for Hand Force inRight Angle Nutrunner Operation

SEOUNGYEON A. OR, Samsung Data Systems Co., Ltd., Seoul, Korea, and ROBERT G. RADWIN1and FRANK J. FRONCZAK,University of Wisconsin, Madison, Wisconsin

A deterministic mechanical model based on physical tool parameters was used forestimating static and dynamic hand forces from kinematic measurements. We in-vestigated the effects of target torque (25, 40, and 55 Nm) and threaded fastener jointhardness (35-, 150-, 300-, 500-, and 900-ms torque buildup time) on hand force.Estimated hand force was affected by target torque and joint hardness. Peak andaverage dynamic hand force was least for the hard joint (35-ms buildup) and great-est for the medium hardness joint (l50-ms buildup). Tool inertia played the majorrole in reducing hand reaction force. Estimated hand force decreased when theinertial force component increased. Inertial force decreased by 366% when builduptime increased from 35 to 300 ms. Static modeling overestimated hand force; theerror ranged from 10% for a soft joint to 40% for a hard joint. Results from directhand force measurements using a strain gauge dynamometer showed that the dy-namic model overestimated peak hand force by 9%. However, average hand forceand force impulse were not significantly overestimated.

INTRODUCTION

Power nutrunners are widely used in manufac-turing because of their ability to tighten threadedfasteners rapidly, their capacity to generate hightorque, and their reliability in achieving targettorque levels. Joint tightening is dependent onthe operator's capacity to react against spindletorque, because torque can build only if there isopposing force at the handle generated by theoperator, by the inertia of the tool and hand, orby an accessory such as a torque reaction bar. Toensure the quality of the operation and the safetyof the operator, it is important for the operator tobe able to react against reaction forces transmit-

1 Requests for reprints should be sent to Robert G. Radwin,Department of Industrial Engineering, University of Wisconsin-Madison, 1513 University Ave., Madison, WI 53706.

ted to the handle. If the building torque reactionforce overpowers the operator's strength, thenthe tool will snap the operator's hand in the di-rection of the torque reaction, away from the op-erator (Oh & Radwin, 1997). When the operatorcannot react against this torque, there may not beenough torque to fasten a joint, potentially caus-ing a failed assembly and in some cases resultingin an accident or injury.

Forceful exertions have been related to physi-cal stress, including fatigue and musculoskeletaldisorders of the upper limb (Armstrong, Radwin,Hansen, & Kennedy, 1986; Silverstein, Fine, &Armstrong, 1987). In order to minimize operatorexertions it is necessary to identify and under-stand the factors that influence forces actingagainst the operator. Several methods have beenused to directly measure forces during tool op-eration. They include direct measurement,

© 1997, Human Factors and Ergonomics Society. All rights reserved.

498-September 1997

electromyography (EMG), and subjective assess-ment. Force or pressure sensors mounted at thepoint of force application (Fellows & Freivalds,1989; Oh & Radwin, 1993; Radwin, Oh, Jensen, &Webster, 1992) involve direct force measurementbut require custom sensors and tool modifica-tions. Electromyography (Basmajian 1985; Bou-isset, 1973) can be used to estimate applied handforce; however, the relationship between EMGand muscle exertions involving dynamic move-ment is not well understood. As an indirect mea-surement, subjective ratings of perceived exer-tion are sometimes used to identify conditionsthat minimize perceived force exertion level(Ulin, Snook, Armstrong, & Herrin, 1992).

Required hand force can sometimes be es-timated under the assumption of static equi-librium (Radwin, VanBergeijk, & Armstrong,1989; Radwin, Oh, & Fronczak, 1995). Whenconsiderable hand movement occurs during tooloperation, the hand force estimated using staticmodels may be less accurate because of inertialeffects. In this case, a dynamic mechanical modelmay provide a more accurate hand force estima-tion. The goals of this study were to construct asimple deterministic dynamic mechanical modelfor estimating hand forces during power nutrun-ner operation and to examine how these forcesvary when the tool is operated under differentcombinations of target torque and joint hardness.

METHODS

Dynamic Model

We developed a dynamic mechanical model forright-angle nutrunner operation in the horizontalplane in which the longitudinal axis of the toolspindle was perpendicular to the ground. TheCartesian coordinate system used was relative tothe orientation of the hand and consistent withthe International Standards Organization basi-centric (ISO 5349, 1986) coordinates (see Figure1). The origin (0) was arbitrarily taken as theintersection between the line passing through thelongitudinal axis of the spindle and the y-z planeat the end of the socket. All dimensions were

HUMAN FACTORS

Side View

xy.J

Figure 1. External coplanar forces acting on a rightangle power hand tool.

measured from this origin, and moments werecalculated with respect to the origin (unless oth-erwise specified). Torque in the clockwise direc-tion about the spindle was defined as positivewhen facing the threaded fastener head.

As described by Radwin et al. (1989, 1995), un-der the assumption of static equilibrium, statichand reaction force at a given time can be calcu-lated as torque at the spindle divided by thehandle length:

in which F = force, H = hand, T = torque, and L =length. Using the equations of motion, the follow-ing system of equations describe the dynamichand forces and moments:

in which M = moment, W = weight, subscript T(T) = tool, I = moment of inertia, m = mass, and a= angular acceleration. The detailed model canbe found in Oh (1995). Hand reaction force (FHZ)and tool support force (FHJ can be determinedby solving Equation 1 and Equation 2:

DYNAMICHAND FORCE IN TOOL OPERATION September 1997-499

(3)TABLE 1

ToolParameters

Experimental Design

The three-factor full-factorial experimental de-sign included target torque (T), torque builduptime (B), and subject (S). Subject was considereda random variable, and torque and torquebuildup time were fixed variables. All combina-tions of three target torques (25, 40, and 55 Nm)and five torque buildup times (35, 150, 300, 500,and 900 ms) were presented randomly to every

head was perpendicular to the ground were usedfor this study.

A Penny & Giles flexible electrogoniometerwas used for measuring angular handle displace-ment (ll)about the spindle. Angular data weresampled using a 12-bit analog-digital converter ata sample rate of 500 Hz. First and second deriva-tives of EI were taken in order to calculate angularvelocity and angular acceleration, respectively. Adigital low-pass filter with a cutoff frequency of55 Hz was used to reduce signal noise. The aver-age mass of the hand and lower arm was approxi-mated as 1.6 kg, according to Dempster (1955).The tool CG was estimated as 0.21 m measuredfrom the tool spindle (Drillis, Schneck, & Gage,1963). The mass moment of inertia of the tool(1'001) was measured using the quick-releasemethod (Bouisset & Pertuzon, 1968; Drillis, Con-tini, & Bluestein, 1964). A total of 10 trials weremade to estimate 1'001' The average was 0.3003kg· m2 (SD = 0.0198 kg· m2).

58.5 em

21.0 em

0.3003 kg/m2

48.0 em11.5 cm

37 N220 revolutions/min

30 to 100 Nm

• Measured in the laboratory.

Tool lengthSpindle to center of grip

lengthHandle circumferenceWeightFree speedTorque rangeCenter of gravity location

from the spindleaTool inertia with respect to

the spindle8

Parameter

Equipment

Hand reaction force (FHz) during tool opera-tion was calculated, based on the mode describedin Equation 4, by substituting geometric and in-ertial parameters of the power hand tool studiedand using kinematic data collected in a previousinvestigation (Oh & Radwin, in press).

A computer-controlled power hand tool wasused to study hand tool operation in the labora-tory. An Atlas Copco Tensor right angle nutrun-ner (ETV-GI00-L13N-CTAD)was operated on anIndresco joint simulator. The tool contained atorque transducer and an angle encoder inte-grated into the spindle head, which outputted sig-nals representing applied torque (Tnu,) and angu-lar spindle rotation. Specific tool parameters arelisted in Table 1. A detailed description of theequipment is provided in Oh and Radwin (1997).Data for only tool operation in a horizontal work-station where the longitudinal axis of the joint

Several simplifying assumptions were made. Itwas assumed that forces could be summed alongthe handle without producing coupling mo-ments. This assumption allowed hand force to beconsidered as a single point of application. Thehand and lower arm mass was considered a pointmass, and hand force was concentrated at thecenter of the grip, which coincided with the cen-ter of gravity (CG) of the hand. This assumptionenabled the moment of inertia of the hand to bezero at its eG. Only hand force components re-acting against torque (FHz) and supporting thetool (F Hx) were considered in the model. Thehand force in the y direction was assumed to beinsignificant; furthermore, it was assumed thatthe hand does not create torque along the y axis,which means that there was no twisting motionby wrist flexion or extension during tool opera-tion. Frictional forces were also ignored.

SOO-September 1997

participant. Ten replicates were made for eachexperimental condition, and the last five trialswere used for data analysis in order to reducelearning effects. Six inexperienced volunteers(three men and three women) participated. Theparticipants' average age was 21 years (SD = 1.5years), average stature was 167 cm (SD = 12 cm),and average body weight was 72 kg (SD = 23 kg).

Dependent Variables

Representative torque, hand angular accelera-tion, and hand force records are illustrated inFigure 2. Inertial torque was calculated from an-gular acceleration measurements and by inertiaof the tool and hand. Inertial force was defined bythe ratio of inertial torque and the tool handlelength (0.48 m). Peak inertial force during torquebuildup in the positive direction (PIP) and after

HUMAN FACTORS

shutoff in the negative direction (PIN) were de-termined. Four dependent variables were mea-sured for investigating target torque and builduptime effects on FHv including peak force duringbuildup (PFP), average force during buildup(AFP), force impulse during buildup (IFP), andpeak hand force after shutoff (PFS). The errorbetween FHz estimated using the static mechani-cal model and the dynamic mechanical model,Fcnw' was calculated as

Fcrror(%) =Hand Forcestatic - Hand FOrCedynamic------------x 100.

Hand ForCestatic

Repeated-measures analysis of variance(ANOVA) was used to determine statistically sig-nificant effects for hand reaction force, inertial

35ms 150 ms 300 ms 500 ms 900 msQ):::J-o-E"'20_~

c-o2.--13Q)nseQ)oa:LL

-.CJ>Q)1J>~-"-0.-0.!Q ~0-

100~o ...•

·100

2.5~o ~ "

-2.5

0.1:1 ""-0.08 j

012

Time (s)

AIf'

o 1 2Time (s)

J\ •.V~

ILo 2

Time (s)012

Time (s)012

Time (s)Figure 2. Representative reaction torque at the spindle, hand reaction force estimated using the dynamic model,handle acceleration, handle velocity, and handle displacement.

DYNAMIC HAND FORCE IN TOOL OPERATION

force, and Ferror. Post-hoc Tukey pairwise con-trast tests were used for selected significant ef-fects. All statistical analysis was performed usingBMDP statistical software.

Model Validation

The validity of the dynamic model was testedby comparing direcdy measured hand reactionforce with the hand reaction force estimated us-ing the model. An aluminum strain gauge dyna-mometer (Radwin, Masters, & Lupton, 1991)weighing 0.1 kg was rigidly attached at the end ofthe nutrunner handle and grasped by the opera-tor. The addition of the dynamometer extendedthe distance between the hand and spindle (LH)to 0.67 m. Ten operations were performed forboth a hard joint (35-ms buildup) and a soft joint(900-ms buildup). Target torque was fixed at 55Nm. Peak and average hand force, as well as forceimpulse during torque buildup, were calculated.Repeated-measures ANOVA was used to deter-mine the significant effects of tool dynamics onhand reaction force.

RESULTS

Inertial Force from Tool and Hand Mass Momentof Inertia

The ANOVA F statistics and corresponding pvalues for the main and interaction effects aresummarized in Table 2. Peak inertial force duringtorque buildup (PIP) was significandy influenced

TABLE 2

September 1997-501

by target torque and torque buildup time. On av-erage, PIP increased by 76% as target torque in-creased from 25 to 55 Nm (see Table 3). Torquebuildup time and the interaction of T x B (seeFigure 3) had a significant effect on PIP. A posthoc Tukey test indicated that there was a signifi-cant decrement in PIP as buildup time increasedfrom 35 to 150 ms for all three torque levels (p <.01). When torque buildup time was greater thanor equal to 300 ms, PIP for 40 and for 55 Nmtorque did not significandy change (p > .05).

Target torque had a significant effect on peakinertial force after shutoff (PIN). As torque in-creased from 25 to 55 Nm, the magnitude of PINincreased by 89% (see Table 3). Torque builduptime also had a significant effect on PIN (see Fig-ure 4). A Tukey pairwise test demonstrated thatthe magnitude of PIN was greatest for a 35-msbuildup time (p < .01). The T x B interaction wasnot statistically significant for PIN (p > .01).

Hand Force

Torque, buildup time, and T x B had signifi-cant effects on peak hand force (PFP), averagehand force (AFP), and force impulse (IFP) duringthe torque buildup phase. When torque increasedfrom 25 to 55 Nm, PFP increased by 108%,AFP increased by 103%, and IFP increased by126% (see Table 3). Torque buildup time and T xB effects on PFP, AFP, and IFP were also signifi-cant (see Figure 3). Tukey pairwise contrasts

Summary of F Statistics and p Values for SignificantMain Effects and Interactions

Effect

Torque Build-upTime TxBDependentVariable Unit F(2,10) p F(4,20) P F(8,450) P

PIP N 29.9

S02-September 1997 HUMAN FACTORS

TABLE 3

Summary Statistics for Significant Torque Effects (mean and SD in parentheses)

DependentTarget Torque

Variable Unit 25Nm 40Nm 55Nm

PIP N 10.4 (7.3) 13.4 (9.9) 18.2 (13.2)PIN N -11.9 (4.8) -18.0 (7.7) -23.3 (9.4)PFP N 57.8 (13.2) 88.3 (21.8) 120.0 (28.4)AFP N 24.1 (6.2) 35.4 (12.0) 49.0 (17.2)IFP Ns 9.9 (6.9) 16.8 (12.4) 22.4 (17.1)PFS N 31.0 (12.5) 41.8 (20.7) 53.6 (23.1)Ferror % 20.1 (14.5) 16.5 (12.7) 16.1 (12.4)

Note: NS = newton seconds

demonstrated that PFP was significantly greaterfor the lSO-ms buildup time (p < .01). PFP did notsignificantly differ for buildup times 300 ms orgreater for all three torque levels (p > .05). PFPwas significantly less (p < .05) for the 3S-msbuildup time than for the other buildup timeswhen target torque was 40 and 55 Nm. APP in-

creased significantly as buildup time increasedfrom 35 to 150 ms (p < .01) for all three torquelevels (see Figure 3). AFP remained relativelyconstant for the buildup times 300 ms or greater(p < .01) for all torque levels. Furthermore, AFPwas not significantly affected by target torque forthe 35-ms buildup time (p > .1). IFP was least for

Build-up Time (ms)

40

~Q)

~0u.iii 20'EQ)

E

0a 300 600 900

150

~Q) 100~ou.~ 50Q)

a..

Target Torque

o 55Nm• 40Nm[] 25Nm

300 600 900Build-up Time (ms)

Target Torque

o 55Nm• 40NmC 25Nm

80 50

~Ul~

Q) Q)

~ III'30 a.U. 40 .E 25Q)Ol Q)III u•...

LL«a0 300 600 900 300 600 900

Build-up Time (ms) Build-up Time (ms)

Figure 3. Significant torque and buildup time interaction for peak inertial force, peak hand force, average handforce, and force impulse during torque buildup.

DYNAMICHAND FORCE IN TOOL OPERATION September 1997-503

Figure 4. Peak inertial force and peak hand force aftershutoff were influenced by buildup time. As builduptime increased from 35 to 150 ms, the magnitude ofPIN and PFS decreased (error bars represent one stan-dard deviation).

6O~~

30 1 1 r r

Build-up Time (ms)

time (soft joint) than for the 35-ms buildup time(hard joint; see Figure 6). Similarly, peak dy-namic hand force, F(1, 5) = 254, p < .01, averagedynamic hand force, F(1, 5) = 228, p < .01, anddynamic impulse, F(1, 5) = 3854, p < .01, weregreater for the soft joint than for the hard joint.Peak hand force estimated for the static modelwas significantly greater than for the dynamicmodel, F(1, 9) = 165, p < .01, or for measuredhand force F(1, 9) = 731, P < .01. Average peakstatic hand force was 13% greater than dynamicpeak hand force and 26% greater than measuredhand force. The dynamic model overestimatedpeak hand force, F(1, 9) = 181, p < .01, by 15.7 N(SD = 2.7 N) for the hard joint and by 4.7 N (SD= 3.6 N) for the soft joint. Force impulse, t(19) =-1.9, P > .05, and average force, t(19) = -1.9, p >.05, were not significantly different whether mea-sured directly or estimated using the dynamicmodel.

r

900600

o Peak Hand Force• Peak Inertial Force

300-60

o

-30

Q) 0o•...ou.

-z.......•

DISCUSSION

Figure 5. Significant buildup time effect on the differ-ence between the hand force estimated using the dy-namic model and the hand force estimated under theassumption of static equilibrium.

This study demonstrates that a simple dynamicmechanical model can be used for estimatinghand force during right-angle nutrunner opera-tion and that the estimated hand force was af-fected by tool dynamics parameters, includingtarget torque and buildup time. Estimated peakand average hand force (PFP and AFP) were less

o 300 600 900Build-up Time (ms)

o

60

40

20

-cfl.-~e~Q)

LL

the 35-ms buildup time and greatest for the 900-ms buildup time for all three torque levels (p< .01).

PFS was significantly affected by torque andtorque buildup time. As torque increased from 25to 55 Nm, PFS increased by 73% (Table 2). ATukey pairwise contrast test showed that PFS forthe 35-ms buildup time was significantly greater(p < .01) than PFS for other buildup times (seeFigure 4).

Ferror was significantly affected by torque andbuildup time. As torque increased from 25 to 55Nm, Ferror decreased by 25% (see Table 3). Thepost hoc Tukey pairwise contrast test showedthat FerO'Or was greatest for the 35-ms builduptime, followed by Fen-or for the 150-ms builduptime (p < .05; see Figure 5).

Model Validation

Static Model versus Dynamic Model

Peak hand force, F(1, 5) = 485, P < .01, averagehand force, F(1, 5) = 898, P < .01, and impulseF(1, 5) = 3030, P < .01, measured at the handlewere significantly greater for the 900-ms buildup

S04-September 1997 HUMAN FACTORS

~100

?0>~ 750u. o Static Estimation"0 50I:: C Dynamic EstimationctlI 25 • Measured Force~ctl0> 0a.

0 300 600 900Build-up Time (ms)

~ ]000> 0 Static Estimation~0 75 C Dynamic Estimationu.

"0 50 • Measured ForceI::ctl

~I0> 25Cl~0> 0>« 0 300 600 900

Build-up Time (ms)

the static model was that it could not estimateforce acting on the hand after tool shutoff. Con-siderable hand force was observed after tool shut-off (see Figure 4).

It was anticipated that the greater the tool in-ertia, the more reaction torque it is capable ofabsorbing. Ignoring the hand and arm, the mo-ment at the spindle, Mo(t), is equal to the inertiaof the tool with respect to the spindle multipliedby the tool angular acceleration:

Given that torque builds up linearly with respectto time, the moment at the spindle can be ex-pressed as

(5)

for which c is the torque buildup rate (in newtonmeters per second), and t is time (in seconds).For any given target torque, c is greater for short

1.0

c = 50 Nmls

0.5 \.0

0.5Time(s)

c=1000 Nm/s

50 c = 1000 Nmls

ao

E6~ 25f?"oI-

20000c2N"'01 '"Cii:o 10000Qieo~o«

0.211"/&,... 0.3

•'Iii(!rOI?7 30(/)

'3 o Static EstimationCo 20E C Dynamic Estimation0> 10 • Measured Forcee0u.

for the smaller target torque (25 Nm) and forhard joints (35-ms buildup time). Both PFP andAFP increased markedly as buildup time in-creased from 35 to 150 ms.

Inertial effects should be considered when mo-tion is involved. The estimated hand force usingthe dynamic model was 60% to 90% of the esti-mated hand force for the static model, dependingon the buildup time. The static model did notaccount for the effect of torque rate and builduptime, which had a significant effect on estimatedhand force (see Figure 3). Another limitation of

300 600 900

Build-up Time (ms)

Figure 6. Peak hand force, average hand force, andforce impulse measured directly and estimated by thestatic and dynamic models.

DYNAMICHAND FORCE IN TOOL OPERATION September 1997-505

torque buildup times and less for long torquebuildup times (see Figure 7). Equation S can bewritten in terms of tool acceleration as

Equation 6 shows that tool acceleration is in-versely proportional to the tool inertia and is pro-portional to c and t (see Figure 7).

Increasing the inertia of the tool results in lessangular acceleration, but increasing the tool in-ertia by augmenting its mass gives rise to a trade-off. When the tool inertia was less than 0.3kg . m2, angular acceleration was substantiallylessened by increasing its inertia, but when thetool inertia was greater than 0.3 kg' m2, in-creased inertia did not result in a significant re-duction in angular acceleration (see Figure 7).Even if substantial angular acceleration is re-duced, adding tool mass increases the static toolsupport force requirement (see Equation 3).

The hand force estimate in Equation 4 requiredan estimation of hand and arm mass. In order tosimplify the model, we assumed that only themass of the hand and forearm acted on the tooland that the CG of the hand and forearm coin-cided with the center of the grip. Although thedynamic model included inertial effects of thetool, hand, and forearm, the validation studyshowed that inertial effects were somewhat un-derestimated, resulting in slightly greater peakhand force estimates using the dynamic model.Parts of the upper arm and body mass shouldalso contribute to the mass acting on the tool;this contribution depends on the posture and po-sition of the operator. Future models should ac-count for force components affected by operatorposture and orientation with respect to the tool.

Equation 6 shows that angular acceleration in-creases as torque buildup rate increases. Longertorque buildup times resulted in less accelera-tion. This may explain why inertial force, whichis proportional to hand acceleration, was greaterfor the 3S-ms buildup time. Aprevious study (Oh& Radwin, in press) observed that greater peakhandle velocities and accelerations were associ-

cta(t) =-

1'001(6)

ated with the 3S-ms buildup time, whereas lesshandle displacement occurred under identical ex-perimental conditions. Because handle accelera-tion and velocity associated with soft joints wereless than that for hard joints (Oh & Radwin, inpress), the inertial force provided by the tool de-creased, requiring greater hand force.

The 3S-ms buildup time may have some advan-tage over longer torque buildup times. Greaterhandle acceleration increases the inertial contri-bution for absorbing torque reaction force (seeFigure 3). Consequently, the operator exerts lesshand force during torque buildup. In addition,operator capacity to react against tool forces isenhanced by increased maximum voluntary con-traction when eccentric hand velocity increases(Hortobagyi & Katch, 1990; Oh & Radwin, 1997);however, the health consequences of eccentriccontraction are not known. Although hand reac-tion force was less for a hard joint, greater peaktorque variance was associated with hard joints(Oh & Radwin, in press). A joint could be "soft-ened" by slowing the power hand tool spindlespeed in order to improve torque accuracy at atrade-off of increased hand force.

Oh and Radwin (in press) observed thatmedium-hardness joints were related to greaterhandle instability as well as greater muscularcontraction for the same tool as in the currentstudy. Because the tool angular acceleration as-sociated with the medium joints decreased sig-nificantly as buildup time increased from 3S toISOms, the model predicted that the hand forcewould be greater for the 1S0-msbuildup time andthe same target torque. The joint considered"hard" (SOO-mstorque buildup time) in Radwinet al. (1989) was in fact a medium-hardness joint,which may explain why greater exertions wereobserved for a "hard" joint than for a soft joint(2-s torque buildup time, which is contrary to thecurrent study findings).

Oh and Radwin (in press) observed from fore-arm muscle EMG latency that contraction formedium joints was not initiated until 64% of thetarget torque had already built up. Consequently,the greater handle instability observed for me-dium joints could be related to an absence of the

S06-September 1997

benefit of early muscle contractions for control-ling the tool, in addition to decreased inertialforce, as evidenced in the current study. Thegreater instability for medium-hardness jointsmight also be attributable to a theorized me-chanical resonance that amplifies hand motion(velocity and displacement) in the tool-operatorsystem resulting in greater handle instability (asproposed by Lindqvist, 1993).

ACKNOWLEDGMENTS

This work was sponsored in part by grant No. DMII-9158136from the National Science Foundation and by matching giftsfrom industry.

REFERENCES

Armstrong, T. J., Radwin, R. G., Hansen, D. J., & Kennedy, K. W.(1986). Repetitive trauma disorders: Job evaluation and de-sign. Human Factors, 28, 325-336.

Basmajian, J. V. (1985). Muscles alive: Their functions revealedby electromyography (5th ed.). Baltimore: Williams &Wilkins.

Bouisset, S., & Pertuzon, E. (1968). Experimental determina-tion of the moment of inertia of limb segment. In J. Warten-weiler, E. Jokl, & M. Hebbelinck (Eds.), Biomechanics I (pp.106-109). New York: Karger.

Bouisset, S. (1973). EMG and muscle force in normal motoractivities. New Developments in Electromyography and Clini-cal Neurophysiology, I, 547-583.

Dempster, W. T. (1955). Space requirements of the seated opera-tor (Tech. Report WADC-TR-55-159). Wright-PattersonAFB, OH: Aerospace Medical Research Laboratories.

Drillis, R., Schneck, D., & Gage, H. (1963). The theory of strik-ing tools. Human Factors, 5, 467-478.

Drillis, R., Contini, R., & Bluestein, M. (1964). Body segmentsparameters: A survey of measurement technique. ArtificialLimbs, 8, 44-66.

Fellows, G. L., & Freivalds, A. (1989). The use of force sensingresistors in ergonomic tool design. In Proceedings of theHuman Factors Society 33rd Annual Meeting (pp. 713-717). Santa Monica, CA: Human Factors and ErgonomicsSociety.

Hortobagyi, T. & Katch, F. 1. (1990). Eccentric and concentrictorque-velocity relationships during arm flexion and exten-sion: Influence of strength level. European Journal of Ap-plied Physiology, 60, 395-40 I.

International Standards Organization. (1986). Mechanical vi-bration-Guidelines for the measurement and the assessmentof hwnan exposure to hand-transmitted vibration (ISO 5349-1986). New York: Author.

HUMAN FACTORS

Lindqvist, B. (1993). Torque reaction force reaction in anglednutrunners. Applied Ergonomics, 24, 174-180.

Oh, S. (1995). Tool dynamics and workstation effects on powerhand tool operation. Unpublished doctoral dissertation,University of Wisconsin-Madison, Madison, WI.

Oh, S., & Radwin, R. G. (in press). The influence of targettorque and torque build-up time on physical stress in rightangle nutrunner operation. Ergonomics.

Oh, S., & Radwin, R. G. (1993). Pistol grip power tool handleand trigger size effects on grip exertions and operator pref-erence. Human Factors, 35, 551-569.

Oh, S., & Radwin, R. G. (1997). The effects of power hand tooldynamics and workstation design on handle kinematics andmuscle activity. International Journal of Industrial Ergo-nomics, 20(1), 59-74.

Radwin, R. G., Masters, G. P., & Lupton, F. W. (1991). A linearforce-summing hand dynamometer independent on pointof application. Applied Ergonomics, 22, 339-345.

Radwin, R. G., Oh, S., & Fronczak, F. J. (1995). A mechanicalmodel of hand force in power hand tool operation. In Pro-ceedings of the Human Factors and Ergonomics Society 39thAnnual Meeting (pp. 548-552). Santa Monica, CA: HumanFactors and Ergonomics Society.

Radwin, R. G., Oh, S., Jensen, T. R., & Webster, J. G. (1992).External finger forces in submaximal five-finger staticpinch prehension, Ergonomics, 35, 275-288.

Radwin, R. G., VanBergeijk, E., & Armstrong, T. J. (1989).Muscle response to pneumatic hand tool torque reactionforce reaction forces. Ergonomics, 32, 655-673.

Silverstein, B. A., Fine, 1.., & Armstrong, T. J. (1987). Occupa-tional factors and carpal tunnel syndrome. American Jour-nal of Industrial Medicine, 11, 343-358.

Ulin, S. S., Snook, S. H., Armstrong, T. J., & Herrin, G. D.(1992). Preferred tool shapes for various horizontal and ver-tical work locations. Applied Occupational and EnvironmeJt-tal Hygiene, 7, 327-337.

Seoungyeon A. Oh is a consultant at Samsung Data SystemsCo., Ltd., in Seoul, Korea. She received her Ph.D. in industrialengineering ITom the University of Wisconsin-Madison.

Robert G. Radwin is chair of the Biomedical Engineering Pro-gram and a professor in the Department of Industrial Engineer-ing at the University of Wisconsin-Madison. He received hisPh.D. in industrial and operations engineering (ron1 the Uni-versity of Michigan, where he was a postdoctoral research fel-low at the Center for Ergonomics.

Frank J. Fronczak is an associate professor of mechanical en-gineering at the University of Wisconsin-Madison. He receivedhis D.E. (doctor of engineering) degree ITom the University ofKansas in mechanical engineering design.

Date received: March 10, 1996Date accepted: February 10, 1997