ABSTRACT
While computers excel at augmenting user's cognitive abilities, only recently we started utilizing their full potential to enhance our physical abilities. More and more wearable force-feedback devices have been developed based on exoskeletons, electrical muscle stimulation (EMS) or pneumatic actuators. The latter, pneumatic-based artificial muscles, are of particular interest since they strike an interesting balance: lighter than exoskeletons and more precise than EMS. However, the promise of using artificial muscles to actually support skill acquisition and training users is still lacking empirical validation.
In this paper, we unveil how pneumatic artificial muscles impact skill acquisition, using two-handed drumming as an example use case. To understand this, we conducted a user study comparing participants' drumming performance after training with the audio or with our artificial-muscle setup. Our haptic system is comprised of four pneumatic muscles and is capable of actuating the user's forearm to drum accurately up to 80 bpm. We show that pneumatic muscles improve participants' correct recall of drumming patterns significantly when compared to auditory training.
- Massimo Cenciarini and Aaron M Dollar. 2011. Biomechanical considerations in the design of lower limb exoskeletons. In 2011 IEEE International Conference on Rehabilitation Robotics. IEEE, 1--6.Google ScholarCross Ref
- Frank Daerden and Dirk Lefeber. 2002. Pneumatic artificial muscles: actuators for robotics and automation. European journal of mechanical and environmental engineering 47, 1 (2002), 11--21.Google Scholar
- Swagata Das, Yusuke Kishishita, Toshio Tsuji, Cassie Lowell, Kazunori Ogawa, and Yuichi Kurita. 2018. ForceHand glove: a wearable force-feedback glove with pneumatic artificial muscles (PAMs). IEEE Robotics and Automation Letters 3, 3 (2018), 2416--2423.Google ScholarCross Ref
- David Feygin, Madeleine Keehner, and R Tendick. 2002. Haptic guidance: Experimental evaluation of a haptic training method for a perceptual motor skill. In Proceedings 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. HAPTICS 2002. IEEE, 40--47.Google ScholarCross Ref
- Katsuya Fujii, Sophia S Russo, Pattie Maes, and Jun Rekimoto. 2015. MoveMe: 3D haptic support for a musical instrument. In Proceedings of the 12th International Conference on Advances in Computer Entertainment Technology. ACM, 9.Google ScholarDigital Library
- Shinya Fujii, Kazutoshi Kudo, Tatsuyuki Ohtsuki, and Shingo Oda. 2009. Tapping performance and underlying wrist muscle activity of non-drummers, drummers, and the world's fastest drummer. Neuroscience letters 459, 2 (2009), 69--73.Google Scholar
- Shinya Fujii, Kazutoshi Kudo, Masahiro Shinya, Tatsuyuki Ohtsuki, and Shingo Oda. 2009. Wrist muscle activity during rapid unimanual tapping with a drumstick in drummers and nondrummers. Motor Control 13, 3 (2009), 237--250.Google ScholarCross Ref
- Shinya Fujii and Shingo Oda. 2006. Tapping speed asymmetry in drummers for single-hand tapping with a stick. Perceptual and motor skills 103, 1 (2006), 265--272.Google Scholar
- Ashraf S Gorgey. 2018. Robotic exoskeletons: The current pros and cons. World journal of orthopedics 9, 9 (2018), 112.Google Scholar
- Takashi Goto, Swagata Das, Yuichi Kurita, and Kai Kunze. 2018. Artificial Motion Guidance: an Intuitive Device based on Pneumatic Gel Muscle (PGM). In The 31st Annual ACM Symposium on User Interface Software and Technology Adjunct Proceedings. ACM, 182--184.Google ScholarDigital Library
- Xiaochi Gu, Yifei Zhang, Weize Sun, Yuanzhe Bian, Dao Zhou, and Per Ola Kristensson. 2016. Dexmo: An Inexpensive and Lightweight Mechanical Exoskeleton for Motion Capture and Force Feedback in VR. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16). ACM, New York, NY, USA, 1991-1995. https://doi.org/10.1145/2858036.2858487Google ScholarDigital Library
- Mark A Guadagnoli and Timothy D Lee. 2004. Challenge point: a framework for conceptualizing the effects of various practice conditions in motor learning. Journal of motor behavior 36, 2 (2004), 212--224.Google ScholarCross Ref
- Yasuhisa Hasegawa, Yasuyuki Mikami, Kosuke Watanabe, and Yoshiyuki Sankai. 2008. Five-fingered assistive hand with mechanical compliance of human finger. In 2008 IEEE international conference on robotics and automation. IEEE, 718--724.Google ScholarCross Ref
- Ai Higuchi, Junichiro Shiraishi, Yuichi Kurita, Evgeniia Shchelkanova, Yosuke Ikeda, and Tomohiro Shibata. 2019. Gait Evaluation on Parkinson's Disease Patients Using Spontaneous Stimulus Induced by UPS-PD. In 2019 IEEE/SICE International Symposium on System Integration (SII). IEEE, 412--416.Google ScholarCross Ref
- Simon Holland, Anders J Bouwer, Mathew Dalgelish, and Topi M Hurtig. 2010. Feeling the beat where it counts: fostering multi-limb rhythm skills with the haptic drum kit. In Proceedings of the fourth international conference on Tangible, embedded, and embodied interaction. ACM, 21--28.Google ScholarDigital Library
- Yusuke Kishishita, Swagata Das, Antonio Vega Ramirez, Chetan Thakur, Ramin Tadayon, and Yuichi Kurita. 2019. Muscleblazer: Force-Feedback Suit for Immersive Experience. In 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). IEEE, 1813--1818.Google Scholar
- John W Krakauer and Reza Shadmehr. 2006. Consolidation of motor memory. Trends in neurosciences 29, 1 (2006), 58--64.Google Scholar
- Simon P Landry and François Champoux. 2017. Musicians react faster and are better multisensory integrators. Brain and cognition 111 (2017), 156--162.Google Scholar
- Jaebong Lee and Seungmoon Choi. 2010. Effects of haptic guidance and disturbance on motor learning: Potential advantage of haptic disturbance. In 2010 IEEE Haptics Symposium. IEEE, 335--342.Google ScholarDigital Library
- Ting Liu and Jody L Jensen. 2009. Effectiveness of auditory and visual sensory feedback for children when learning a continuous motor task. Perceptual and motor skills 109, 3 (2009), 804--816.Google Scholar
- Pedro Lopes and Patrick Baudisch. 2013. Muscle-propelled force feedback: bringing force feedback to mobile devices. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2577--2580.Google ScholarDigital Library
- Pedro Lopes and Patrick Baudisch. 2017. Immense Power in a Tiny Package: Wearables Based on Electrical Muscle Stimulation. IEEE Pervasive Computing 16, 3 (2017), 12--16.Google ScholarDigital Library
- Pedro Lopes, Patrik Jonell, and Patrick Baudisch. 2015. Affordance++: allowing objects to communicate dynamic use. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 2515--2524.Google ScholarDigital Library
- Pedro Lopes, Sijing You, Lung-Pan Cheng, Sebastian Marwecki, and Patrick Baudisch. 2017. Providing haptics to walls & heavy objects in virtual reality by means of electrical muscle stimulation. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 1471--1482.Google ScholarDigital Library
- Pedro Lopes, Sijing You, Alexandra Ion, and Patrick Baudisch. 2018. Adding force feedback to mixed reality experiences and games using electrical muscle stimulation. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, 446.Google ScholarDigital Library
- Laura Marchal-Crespo, Stephanie McHughen, Steven C Cramer, and David J Reinkensmeyer. 2010. The effect of haptic guidance, aging, and initial skill level on motor learning of a steering task. Experimental brain research 201, 2 (2010), 209--220.Google Scholar
- Laura Marchal-Crespo, Peter Wolf, Nicolas Gerig, Georg Rauter, Lukas Jaeger, Heike Vallery, and Robert Riener. 2015. The role of skill level and motor task characteristics on the effectiveness of robotic training: first results. In 2015 IEEE international conference on rehabilitation robotics (ICORR). IEEE, 151--156.Google ScholarCross Ref
- Gary E. McPherson. 2000. Commitment and Practice: Key Ingredients for Achievement during the Early Stages of Learning a Musical Instrument. Bulletin of the Council for Research in Music Education 147 (2000), 122--127. http://www.jstor.org/stable/40319399Google Scholar
- Dan Morris, Hong Tan, Federico Barbagli, Timothy Chang, and Kenneth Salisbury. 2007. Haptic feedback enhances force skill learning. In Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (WHC'07). IEEE, 21--26.Google ScholarDigital Library
- Kazunori Ogawa, Tomohiro Ikeda, and Yuichi Kurita. 2018. Unplugged Powered Suit for Superhuman Tennis. In 2018 12th France-Japan and 10th Europe-Asia Congress on Mechatronics. IEEE, 361--364.Google Scholar
- Kazunori Ogawa, Chetan Thakur, Tomohiro Ikeda, Toshio Tsuji, and Yuichi Kurita. 2017. Development of a pneumatic artificial muscle driven by low pressure and its application to the unplugged powered suit. Advanced Robotics 31, 21 (2017), 1135--1143.Google ScholarCross Ref
- Richard Parncutt and Gary McPherson. 2002. The science and psychology of music performance: Creative strategies for teaching and learning. Oxford University Press.Google Scholar
- Wataru Sakoda, Toshio Tsuji, and Yuichi Kurita. 2018. VR Training System of Step Timing for Baseball Batter Using Force Stimulus. In International AsiaHaptics conference. Springer, 321--326.Google Scholar
- Alan W Salmoni, Richard A Schmidt, and Charles B Walter. 1984. Knowledge of results and motor learning: a review and critical reappraisal. Psychological bulletin 95, 3 (1984), 355.Google Scholar
- Richard A Schmidt, Douglas E Young, Stephan Swinnen, and Diane C Shapiro. 1989. Summary knowledge of results for skill acquisition: Support for the guidance hypothesis. Journal of Experimental Psychology: Learning, Memory, and Cognition 15, 2 (1989), 352.Google ScholarCross Ref
- George Lawrence Stone. 2013. Stick control: for the snare drummer. Alfred Music.Google Scholar
- Nobuhiro Takahashi, Hayato Takahashi, and Hideki Koike. 2019. Soft Exoskeleton Glove Enabling Force Feedback for Human-Like Finger Posture Control with 20 Degrees of Freedom. In 2019 IEEE World Haptics Conference (WHC). IEEE, 217--222.Google Scholar
- Emi Tamaki, Takashi Miyaki, and Jun Rekimoto. 2011. Possessed Hand: techniques for controlling human hands using electrical muscles stimuli. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 543--552.Google ScholarDigital Library
- Chetan Thakur, Kazunori Ogawa, Toshio Tsuji, and Yuichi Kurita. 2018. Soft wearable augmented walking suit with pneumatic gel muscles and stance phase detection system to assist gait. IEEE Robotics and Automation Letters 3, 4 (2018), 4257--4264.Google ScholarCross Ref
- Bertrand Tondu. 2012. Modelling of the McKibben artificial muscle: A review. Journal of Intelligent Material Systems and Structures 23, 3 (2012), 225--253.Google ScholarCross Ref
- Eric van Breda, Stijn Verwulgen, Wim Saeys, Katja Wuyts, Thomas Peeters, and Steven Truijen. 2017. Vibrotactile feedback as a tool to improve motor learning and sports performance: a systematic review. BMJ open sport & exercise medicine 3, 1 (2017), e000216.Google Scholar
- Masataka Yamamoto, Yusuke Kishishita, Koji Shimatani, and Yuichi Kurita. 2019. Development of New Soft Wearable Balance Exercise Device Using Pneumatic Gel Muscles. Applied Sciences 9, 15 (2019), 3108.Google ScholarCross Ref
- Adam B Zoss, Hami Kazerooni, and Andrew Chu. 2006. Biomechanical design of the Berkeley lower extremity exoskeleton (BLEEX). IEEE/ASME Transactions on mechatronics 11, 2 (2006), 128--138.Google Scholar
Index Terms
- Accelerating Skill Acquisition of Two-Handed Drumming using Pneumatic Artificial Muscles
Recommendations
Pneumatic artificial muscles based on biomechanical characteristics of human muscles
This article reports the pneumatic artificial muscles based on biomechanical characteristics of human muscles. A wearable device and a rehabilitation robot that assist a human muscle should have characteristics similar to those of human muscle. In ...
A soft exoskeleton suit to reduce muscle fatigue with pneumatic artificial muscles
AH '18: Proceedings of the 9th Augmented Human International ConferenceA major issue at work sites corresponds to aging workers, and the associated back pain. In this research, we develop an assistive suit with light-weight and flexible pneumatic rubber artificial muscles to reduce muscle load. Two assist forces are ...
Bionics Design of Artificial Leg and Experimental Modeling Research of Pneumatic Artificial Muscles
In the research and development of intelligent prosthesis, some of performance test experiments are required. In order to provide an ideal experimental platform for the performance test of intelligent prosthesis, a heterogeneous biped walking ...
Comments