An instrumented object for studying human grasping

This paper proposes the use of an instrumented object for the study of the human grasping strategies. The proposed object is able to measure the grasping forces by means of three Force Sensitive Resistor (FSR) sensors and triaxial acceleration through an accelerometer. The object orientation angles (roll and pitch) can be estimated from the accelerometer output in quasi-static condition, whereas slippage events can be detected through the Power Spectrum Density (PSD) computation of the acceleration on at least one of the three axes. An experimental session on 7 healthy subjects has been performed; each subject used the instrumented object to perform 8 tripod grasp trials. All the sensory information, i.e. applied forces, object orientation and slippage, have been analyzed in order to evaluate the grasping strategies of the different subjects.

[1]  Abd Aziz Mohd Azri,et al.  Accurate and effective method to smoothen grasping force signal of glovemap using gaussian filter , 2013 .

[2]  J. Flanagan,et al.  Modulation of grip force with load force during point-to-point arm movements , 2004, Experimental Brain Research.

[3]  E. Guglielmelli,et al.  A Novel Procedure for In-field Calibration of Sourceless Inertial/Magnetic Orientation Tracking Wearable Devices , 2006, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006..

[4]  Bruno Siciliano,et al.  A bio-inspired grasp optimization algorithm for an anthropomorphic robotic hand , 2012 .

[5]  Manuel G. Catalano,et al.  An instrumented manipulandum for human grasping studies , 2015, 2015 IEEE International Conference on Rehabilitation Robotics (ICORR).

[6]  T. Hasegawa,et al.  A decision method for the placement of mechanical tactile elements for grasp type recognition , 2008, 2008 IEEE Sensors.

[7]  Francesca Cordella,et al.  Development and preliminary testing of an instrumented object for force analysis during grasping , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[8]  Edoardo Battaglia,et al.  ThimbleSense: An individual-digit wearable tactile sensor for experimental grasp studies , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[9]  Helge J. Ritter,et al.  Development of an intelligent object for grasp and manipulation research , 2011, 2011 15th International Conference on Advanced Robotics (ICAR).

[10]  A. Inmann, M. Haugland.  An instrumented object for evaluation of lateral hand grasp during functional tasks , 2001, Journal of medical engineering & technology.

[11]  Gordon Cheng,et al.  Humanoid Multimodal Tactile-Sensing Modules , 2011, IEEE Transactions on Robotics.

[12]  A. Kargov,et al.  A comparison of the grip force distribution in natural hands and in prosthetic hands , 2004, Disability and rehabilitation.

[13]  Francesca Cordella,et al.  Design and development of a sensorized cylindrical object for grasping assessment , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[14]  W D Memberg,et al.  Instrumented objects for quantitative evaluation of hand grasp. , 1997, Journal of rehabilitation research and development.

[15]  Agnès Roby-Brami,et al.  Analysis of grasping strategies and function in hemiparetic patients using an instrumented object , 2013, 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR).

[16]  Patrick E. Crago,et al.  A grasp force and position sensor for the quantitative evaluation of neuroprosthetic hand grasp systems , 1995 .

[17]  Mark R. Cutkosky,et al.  Sensing skin acceleration for slip and texture perception , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[18]  T. Keller,et al.  A SYSTEM FOR MEASURING FINGER FORCES DURING GRASPING , 2000 .

[19]  R. Johansson,et al.  Signals in tactile afferents from the fingers eliciting adaptive motor responses during precision grip , 2004, Experimental Brain Research.

[20]  R S Johansson,et al.  Control of fingertip forces in multidigit manipulation. , 1999, Journal of neurophysiology.

[21]  Nikolaos G. Tsagarakis,et al.  The patched intrinsic tactile object: A tool to investigate human grasps , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.