An Investigation of Hand Force Distribution, Hand Posture and Surface Orientation

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1 An Investigation of Hand Force Distribution, Hand Posture and Surface Orientation R. FIGUEROA and T. ARMSTRONG Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI Abstract This work aims to obtain information and develop models for predicting hand postures that can be incorporated into computerized human manikins. This work is concerned with how finger, wrist, elbow and shoulder postures are affected depending the orientation and magnitude of hand force exerted. The hypotheses included: 1) Object orientation affects upper extremities postures and maximum hand force exertions; 2) Higher force exertions have similar postures per orientation. Shoulder-to-Elbow, Elbow-to- Wrist, Wrist-to-MCP, MCP-to-DP3 vectors were used to determine posture for each condition. Participants performed three exertions (1%, 3% and 1% MVC) perpendicular to an aluminum plate in 45,, 45 and 9 pitch at elbow height. Results show that posture changes depending the force exerted and the threshold for significant changes is at force levels below 5%MVC. Comparing exertions over 5%MVC with exertions of 5%MVC or lower, elbow and wrist angles were significantly greater, and forearm was more perpendicular to the surface. As the force required decreases, the distance between hand and shoulder increases. If lower levels of force are required, a higher clearance is needed to decrease the possibility of acquiring awkward postures, one of the common physical hazards leading to leads to develop MSDs. Project deliverables (hand position, posture, resultant force, contact force distribution, joint moments) can be used to predict upper extremity postures as function of magnitude and orientation of force exerted, these factors can be implemented into computerized human manikins. Keywords: hand posture, force, joint moments, human modeling 1. Introduction The hand is frequently exerted against surfaces to support the body and to hold work objects. These surfaces are often flat, such as a wall or a bench top. Failure to exert sufficient force can result in a fall or a loss of control of the work objects, property damage and injuries. Additionally repeated exertions can result in fatigue or activity related musculoskeletal disorders (MSDs) (Marras et al. 9; Garg and Kapellusch 11). MSDs of hands and fingers are associated with occupational activities across all industrial and service sectors. Upper extremity joint locations and moments are determinant factors to determine the hand posture and hand strength needed to complete a given task. Data and models are needed that can be used to predict the strength capacity of the hand for various work objects and hand postures, and can be used to determine internal forces that contribute to muscle, tendon and nerve disorders (Armstrong 1993). Towards this end, this study aims to understand 1) how maximum forces exerted with the hand against flat surfaces are influenced by posture and surface orientation 2) hand postures by describing the effect of object orientation and force required. Additionally, it examines how forces are distributed between the fingertips and the palm. The resulting force distributions can be used to determine joint moments for biomechanical analysis of tendon and muscle forces. The information obtained in this work, would help in the development of models for predicting hand postures that can be incorporated into computerized human manikins. Modeling of the hand movement is required and used in many fields such as biomechanics, ergonomics, and robotics. Precise generation of motion to manipulate objects of various shape and size is required to help engineers to design optimal product (Miyata et al. 5). Despite of the advances already made in human hand modeling (Choi and Armstrong 7; Kurihara et al. 4), prediction of optimal position and orientation with respect to the object and force needed remains uncertain (Miyata et al. 5). Better posture predictions would lead in the understanding of the required space to reduce the possibility of workers hand injury. 2. Materials and Methods 2.1. Materials The normal contact forces and force distribution were recorded using I-SCAN TM (Tekscan Inc., Boston, MA) at 6 Hz. Two sensors were placed to cover a larger area and were calibrated at pressures of 34.5 kpa and 6.8 kpa (5 PSI and 3 PSI). LabVIEW (National Instruments, Inc., Austin, TX) at 5Hz program was written to show actual force exertion in the display for visual feedback. Data were averaged over 3s during maximum grip rosemfig@umich.edu 1

2 exertions. Statistical analyses were performed using MINITAB Procedure Participants performed three exertions (1%, 3% and 1) perpendicular to an aluminum plate in 45,, 45 and 9 pitch at elbow height (Fig. 1), attached to a force transducer. Exertions were performed using 1) the whole hand (WH) (Fig. 2a) and 2) the fingertips (FT) (Fig. 2c). The independent variables were %MVC and plate orientation. The dependent variables were hand force distribution, finger placements during pushing the plate, and shoulder, elbow and hand postures. Participants were able to get closer to the plate and use their body weight to create more force to have a more realistic scenario. For this first part of the analysis it is assumed that participants exerted the force perpendicular to the surface, thus frictional force is negligible for moment calculation. Plate angle (): Figure 1: Maximum forces were exerted perpendicular to a surface oriented +45, 9, and -45 with respect to horizontal. Frictional force is represented as Fx and normal force as Fy. M wrist F push F x F y =F Mi " # r y # M MCP M PIP M DIP "# # # ####$"# b) M wrist # #$"# r x M MCP M PIP Figure 2: pitch and 1%MVC exertions showing: posture- with (a) WH and (c) FT, and normal force distribution- with (b) WH and (d) FT (red represents highest pressure). Joint moments are represented as M DIP, M PIP, M MCP, M wrist. Six right-handed university students (3 males and 3 females) volunteered to participate in the study and gave written informed consent in accordance with IRB regulations. They were free of known movement disorders. The average stature was ± 5.6 cm for males and ± 3. cm for females. The average hand length was 19.7 ± 1.3 cm for males and 16.8 ±.3 cm for females. The average F y F x M DIP %"# # # ####&"# a) grip strength for the right hand was 457 ± 36 N for males and 299 ± 1 N for females as measured by a Jamar grip dynamometer at position two (49 mm span). The average thumb-index finger pinch strength was 162 ± 13 N for males and 16 ± 13 N for females as measured by a B&L pinch gauge. Since participants exerted the force perpendicular to the surface, frictional force is negligible for moment calculation. Where, " = + "#$% = and Push Force = + = " 3. Results The following vectors were determined to compare postures between the conditions: Shoulder-to- Elbow, Elbow-to-Wrist, Wrist-to-MCP3, MCP3-totip of D3. Were MCP3 is the knuckle joint of the middle finger and tip of D3 is the tip of the middle finger Preliminary Work To obtain preliminary results, two subjects performed five exertions (1%, 75%, 5%, 25% and 5), showing no statistically significant difference in posture among force levels 1%MVC, 75%MVC and 5%MVC. For each plate angle, there was a statistically different posture for 5%MVC, 25%MVC, and 5%MVC. For example, for degree plate using fingertips only, there was a 24.1% (p<.5) change in wrist angle and 1% (p<.5) in elbow angle between 5%MVC and 25%MVC. Also, there was a 13.2% (p<.5) change in wrist angle and 17.9% (p<.5) change in elbow angle between 25%MVC and 5%MVC. Comparing exertions over 5%MVC with exertions of 5%MVC or lower, elbow and wrist angles were significantly greater, and the forearm was more perpendicular to the surface. For further analysis exertions of 1%, 3% and 1% MVC were chosen to perform to compare postures and hand force distribution Force Exertions Table 1 shows a comparison between female and male exertions, for both WH and FT cases, per orientation. Table 1: Average maximum exertions (Newton) per orientation for Females and Males, pushing with the whole hand (WH) and using just the fingertips (FT). Orientation -45 Females Males WH FT WH FT ±3.5 ±4.2 ±6.1 ±

3 45 9 ±7.1 ±7.5 ±2. ± ± ± ± ± ± ± ± ±6.7 On average, Digit 1 had 64.3% higher force for females (Fig. 3) and 52.5% for males (Fig. 4). Figure 3: Female s force distribution per digit (FT- 1%MVC) between orientations. Starting from Digit 1(thumb) to Digit 5 (pinky). 1%MVC (N) 1%MVC (N) Orientation (degrees) Orientation (degrees) Digit 1 Digit 2 Digit 3 Digit 4 Digit 5 Digit 1 Digit 2 Digit 3 Digit 4 Digit 5 Figure 4: Male s force distribution per digit, (FT- 1%MVC) between orientations. Starting from thumb (Digit 1) to pinky (Digit 5). Phalange s joint moments were computed for 4 plate positions for participants 1-3. Results show that MCP has the highest load for all FT and WH cases. WH joint moments were lower than the FT cases, this can be due to the fact that the palm had a high percent of the force distribution (Fig. 2b). For FT cases, joint moment values for pitch were significantly higher (P<.5) in comparison to the rest of the plate orientations. Joint moment ratios were calculated for each joint and clustered by Digit 1 and Digit 2-5 (Table 2), since Digit 1 forces were significantly higher than the rest (Fig. 3 and 4). Table 2: FT case at 1: Observed joint moment ratios for DIP, PIP and MCP joints of participants 1-3. Orientation Digit 1 Digits 2-5 [DIP: MCP] [DIP: PIP: MCP] -45º [1: 2.83] [1: 2.21: 2.26] º [1: 4.32] [1: 2.33: 3.55] 45º [1: 3.59] [1: 2.25: 2.58] 9º [1: 2.63] [1: 1.52: 2.1] 3.3. Posture Analysis When females exerted force with the whole hand, the linear distance from shoulder to the tip of middle finger (Shoulder-to-D3) increased as the %MVC decreased (see Figure 5). Shoulder-to-D3 Figure 5: Female pushing with the whole hand: Average linear distance from shoulder to the tip of middle finger (Shoulder-to-D3 vector) in respect to the percent of force exerted (%MVC). As the %MVC decreased, when participants were asked to push the aluminum plate at 45 and 9 degrees using only the fingertips, the value of Shoulder-to-D3 distance decreased. Figure 6 shows a comparison of the average Shoulder-to-D3 distances in respect to the %MVC by plate orientation. Shoulder-to-D % 3% 1% 1% 3% 1% -45 degrees degrees 45 degrees 9 degrees -45 degrees degrees 45 degrees 9 degrees Figure 6: Female pushing with the fingertip: Average linear distance from shoulder to the tip of middle finger (Shoulder-to-D3 vector) in respect to the percent of force exerted (%MVC). For the fingertips cases, Elbow angle always had a negative value for males and positive values for females among all force levels (see Figure 7). 3

4 Elbow angle Figure 7: Pushing with the fingertips: Average females and males elbow angles at degree pitch in respect to the percent of force exerted (%MVC). 4. Discussion 1% 3% 1% 4.1. Force Exertions Participants were able to get closer to the plate and use their body weight to create more force (as if they are performing a pushing task or supporting their body against a surface) leading to higher exertions at 9 pitch (Table 1). The force magnitude exerted by males was significantly larger (p<.5) than females in and 9 orientations for the WH cases, and in all the orientations for the FT cases (Table 1). There was a positive association between the plate angle and the %MVC (R2 of.97 for females and.83 for males). Since digit 1 (thumb) had a significantly higher force compared to the rest of the phalanges, clearance is needed to ensure space to evade awkward hand postures while supporting their body or pushing against a surface and leaving enough space to accommodate digit 1 to carry the most of the force Posture Analysis Female Male Posture changes depending the force exerted and the threshold for significant changes is at force levels below 5%MVC. As the force required decreases, when participants were asked to push with the whole hand, the distance between the hand and shoulder increased. At pitch, when females were asked to exert a 1%MVC using the whole hand, they used their body weight performing an awkward posture with a negative elbow angle leading to shoulder abduction and high flexion with radial deviation. It is shown by previous studies that deviating wrist flexion and shoulder abduction are some of the worst positions contributing to Upper MSD s (Garg and Kapellusch 11). For all the %MVC cases at pitch, males exerted the force using shoulder abduction. 5. Conclusion Object orientation affects upper extremities postures and maximum hand force exertions. If high %MVC is required and/or large amount of repetitions, surfaces should be able to be adjustable lower than elbow height. This will reduce the possibility of shoulder and elbow abduction, specifically if workers are males. In all the orientations, for exertions higher than 5%MVC, postures were observed to be similar but lower than 5%MVC acquired postures started to change significantly. If lower levels of force are required, a higher clearance is needed, decreasing the possibility of acquiring awkward postures, one of the common physical hazards leading to leads to develop MSDs. This study will help to understand and predict hand postures by describing the effect of object orientation and force required in a given scenario. Next steps include the analysis of contact force distribution and joint moment calculations for the whole hand cases. Also, another six participants will be included in the study to increase the power and proceed to build a reliable posture-predicting model. Additional data will be recorded for the twelve participants asking to push forward against the aluminum plate to include normal and shear forces in the joint moment calculations. Applications of this study includes: designing better workstations and tasks; installation of parts; understand the use of the hands to support the body; positioning 3D human models in virtual environments. Acknowledgement This study was carried out thanks to the financial support of The National Institute for Occupational Safety and Health (NIOSH) and General Motors (GM). References Armstrong T, Buckle P, Fine L, A conceptual model for work-related neck and upper-limb musculoskeletal disorders. Scandinavian journal of work, environment & health, 19(2), Choi J, Grieshaber D, Armstrong T, 7. Estimation of Grasp Envelope Using a 3- Dimensional Kinematic Model of the Hand. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 51(15), Garg A, Kapellusch J, 11. Job Analysis Techniques for Distal Upper Extremity Disorders. Reviews of Human Factors and Ergonomics, 7(1),

5 Kouchi M, Miyata N, Mochimaru M, 5. An Analysis of Hand Measurements for Obtaining Representative Japanese Hand Models, 1 5. Kurihara T, Miyata N, 4. Modeling deformable human hands from medical images. In: Proceedings of the 4 ACM SIGGRAPH/Eurographics symposium on Computer Animation, Marras W, Cutlip R, Burt S, Waters T, 9. National occupational research agenda (NORA) future directions in occupational musculoskeletal disorder health research. Applied ergonomics, (1), Miyata N, Kouchi M, Mochimaru M, Kawachi K, 5. Hand Link Modeling and Motion Generation from Motion Capture Data Based on 3D Joint Kinematics. 5

Development and application of a hand force measurement system

Development and application of a hand force measurement system B.D. Lowe a, Y. Kong b, and J. Han c a National Institute for Occupational Safety and Health, Cincinnati, OH, USA b Systems Management Engineering,