Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand
- PDF / 3,943,680 Bytes
- 16 Pages / 595 x 791 pts Page_size
- 81 Downloads / 199 Views
(2020) 17:116
RESEARCH
Open Access
Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand Cristina Piazza1,2* , Ann M. Simon1,2 , Kristi L. Turner2 , Laura A. Miller1,2 , Manuel G. Catalano3 , Antonio Bicchi3,4 and Levi J. Hargrove1,2,5
Abstract Background: State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently, the translation of neuroscientific theories (i.e. postural synergies) in software and hardware architecture of artificial devices is opening new approaches for the design and control of upper-limb prostheses. Methods: Following these emerging principles, previous research on the SoftHand Pro, which embeds one physical synergy, showed promising results in terms of intuitiveness, robustness, and grasping performance. To explore these principles also in hands with augmented capabilities, this paper describes the SoftHand 2 Pro, a second generation of the device with 19 degrees-of-freedom and a second synergistic layer. After a description of the proposed device, the work explores a continuous switching control method based on a myoelectric pattern recognition classifier. Results: The combined system was validated using standardized assessments with able-bodied and, for the first time, amputee subjects. Results show an average improvement of more than 30% of fine grasp capabilities and about 10% of hand function compared with the first generation SoftHand Pro. Conclusions: Encouraging results suggest how this approach could be a viable way towards the design of more natural, reliable, and intuitive dexterous hands. Keywords: Bionic hand, Adaptive synergies, Soft robotics, Myoelectric control
Introduction Capturing the richness and complexity of the sensorymotor functions of the human hand in a prosthetic device remains one of the challenge in modern science and engineering [1]. State-of-the-art commercial prostheses include sophisticated poly-articular hands, designed to match the appearance and function of human hands through the ingenious combinations of multiple motors and sensors [2]. The classical approach to manage their advanced dexterity consists of using a pair of surface *Correspondence: [email protected] Department of Physical Medicine and Rehabilitation, Northwestern University, 60611 Chicago IL USA 2 The Regenstein Foundation Center for Bionic Medicine, Shirley Ryan AbilityLab, 60611 Chicago IL USA Full list of author information is available at the end of the article 1
electromyographic (sEMG) sensors to control one degree of freedom (DoF) at a time and switch between several motion patterns through different input strategies [3]. Muscles trigger sequences, such as co-contractions [4], are among the most used techniques in commercial devices. Alternative solutions include control through mobile apps, the use of short-range proximity sensors, or, the combination between
Data Loading...
