Glove-based systems for medical applications: review of recent advancements

Human hand motion analysis is attracting researchers in the areas of neuroscience, biomedical engineering, robotics, human-machines interfaces (HMI), human-computer interaction (HCI), and artificial intelligence (AI). Among the others, the fields of medical rehabilitation and physiological assessments are suggesting high impact applications for wearable sensing systems. Glove-based systems are one of the most significant devices in assessing quantities related to hand movements. This paper provides updated survey among the main glove solutions proposed in literature for hand rehabilitation. Then, the process for designing glove-based systems is defined, by including all relevant design issues for researchers and makers. The main goal of the paper is to describe the basics of glove-based systems and to outline their potentialities and limitations. At the same time, roadmap to design and prototype the next generation of these devices is defined, according to the results of previous experiences in the scientific community

Fingertip force estimation via inertial and magnetic sensors in deformable object manipulation

Fingertip contact forces are of utmost importance in evaluating the quality of the human grasp. However, measuring such forces during object manipulation is not a trivial task. In this paper, we propose a novel method to estimate the fingertip contact forces in grasping deformable objects with known shape and stiffness matrix. The proposed approach uses a sensing glove instrumented with inertial and magnetic sensors. Data obtained from the accelerometers and gyroscopes placed on the distal phalanges are used to determine when the fingers establish contacts with the object. The sensing glove is used to estimate the configuration of the hand and the deformation of the object at each contact with the fingertips of the human hand. The force exerted by each fingertip is obtained by multiplying the stiffness matrix of the object and the vector of object's local deformation in the contact point. Extensive simulations have been performed in order to evaluate the robustness of the proposed approach to noisy measurements, and uncertainties in human hand model. In order to validate the proposed approach, experimental validations with a virtual object have been performed. A haptic device was used to generate the contact forces with the virtual object and accurately measure the forces exerted by the users during the interaction