Fingertip Force Research Articles

HaptGlove-Untethered Pneumatic Glove for Multimode Haptic Feedback in Reality-Virtuality Continuum.

Novel haptics technologies are urgently needed to bridge the gap between entirely physical world and fully digital environment to render a more realistic and immersive human-computer interaction. Current virtual reality (VR) haptic gloves either deliver limited haptic feedback or are bulky and heavy. The authors develop a haptic glove or HaptGlove, an untethered and lightweight pneumatic glove, that allows users to "physically" interact in a VR environment and enables both kinesthetic and cutaneous sensations naturally and realistically. Integrated with five pairs of haptic feedback modules and fiber sensors, HaptGlove provides variable stiffness force feedback and fingertip force and vibration feedback, allowing users to touch, press, grasp, squeeze, and pull various virtual objects and feel the dynamic haptic changes. Significant improvements in VR realism and immersion areobserved in a user study with participants achieving 78.9% accuracy in sorting six virtual balls of different stiffnesses. Importantly, HaptGlove facilitates VR training, education, entertainment, and socialization in a reality-virtuality continuum.

A Back-Drivable Rotational Force Actuator for Adaptive Grasping

In this paper, a back-drivable and miniature rotary series elastic actuator (RSEA) is proposed for robotic adaptive grasping. A compact arc grooves design has been proposed to effectively reduce the dimension of the RSEA system. The elastic elements could be reliably embedded in the arc grooves without any additional installation structures. The whole RSEA system is characterized as compact, miniature, and modular. The actuating force is controlled via a PI controller by tracking the deformation trajectory of the elastic elements. An underactuated finger mechanism has been adopted to investigate the effectiveness of the RSEA in robotic adaptive grasping. Results reveal that the underactuated finger mechanism could achieve adaptive grasping via the RSEA in a back-drive approach without the requirement of a fingertip force sensor. The RSEA could also exhibit an actuating compliance and a self-sensing characteristic. The actuating compliance characteristic helps in in guaranteeing the safety of human–robot interaction. The RSEA could estimate the external disturbance due to its self-sensing characteristic, which has the potential to replace the fingertip force sensor in grasping force perception applications.

A haptic illusion created by gravity

Human dexterity requires very fine and efficient control of fingertip forces, which relies on the integration of cutaneous and proprioceptive feedback. Here, we examined the influence of gravity on isometric force control. We trained participants to reproduce isometric vertical forces on a dynamometer held between the thumb and the index finger in normal gravity and tested them during parabolic flight creating phases of microgravity and hypergravity, thereby strongly influencing the motor commands and the proprioceptive feedback. We found that gravity creates the illusion that upward forces are larger than downward forces of the same magnitude. The illusion increased under hypergravity and was abolished under microgravity. Gravity also affected the control of the grip force employed to secure the grasp. These findings suggest that gravity biases the haptic estimation of forces, which has implications for the design of haptic devices to be used during flight or space activities.

Concurrent and Continuous Prediction of Finger Kinetics and Kinematics via Motoneuron Activities.

Robust neural decoding of intended motor output is crucial to enable intuitive control of assistive devices, such as robotic hands, to perform daily tasks. Few existing neural decoders can predict kinetic and kinematic variables simultaneously. The current study developed a continuous neural decoding approach that can concurrently predict fingertip forces and joint angles of multiple fingers. We obtained motoneuron firing activities by decomposing high-density electromyogram (HD EMG) signals of the extrinsic finger muscles. The identified motoneurons were first grouped and then refined specific to each finger (index or middle) and task (finger force and dynamic movement) combination. The refined motoneuron groups (separate matrix) were then applied directly to new EMG data in real-time involving both finger force and dynamic movement tasks produced by both fingers. EMG-amplitude-based prediction was also performed as a comparison. We found that the newly developed decoding approach outperformed the EMG-amplitude method for both finger force and joint angle estimations with a lower prediction error (Force: 3.47±0.43 vs 6.64±0.69% MVC, Joint Angle: 5.40±0.50° vs 12.8±0.65°) and a higher correlation (Force: 0.75±0.02 vs 0.66±0.05, Joint Angle: 0.94±0.01 vs 0.5±0.05) between the estimated and recorded motor output. The performance was also consistent for both fingers. The developed neural decoding algorithm allowed us to accurately and concurrently predict finger forces and joint angles of multiple fingers in real-time. Our approach can enable intuitive interactions with assistive robotic hands, and allow the performance of dexterous hand skills involving both force control tasks and dynamic movement control tasks.

Visual information following object grasp supports digit position variability and swift anticipatory force control.

Anticipatory force control underlying dexterous manipulation has historically been understood to rely on visual object properties and on sensorimotor memories associated with previous experiences with similar objects. However, it is becoming increasingly recognized that anticipatory force control also relies on how an object is grasped. Experiments that allow unconstrained grasp contact points when preventing tilting an object with an off-centered mass show trial-to-trial variations in digit position and subsequent scaling of lift forces, all before feedback of object properties becomes available. Here, we manipulated the availability of visual information before reach onset and after grasp contact (with no vision during the reach) to determine the contribution and timing of visual information processing to the scaling of fingertip forces during dexterous manipulation at flexible contact points. Results showed that anticipatory force control was similarly successful, quantified as an appropriate compensatory torque at lift onset that counters the external torque of an object with a left and right center of mass, irrespective of the timing and availability of visual information. However, the way in which anticipatory force control was achieved varied depending on the availability of visual information. Visual information following grasp contact was associated with greater use of an asymmetric thumb and index finger grasp configuration to generate a compensatory torque and digit position variability, together with faster fingertip force scaling and sensorimotor learning. This result supports the hypothesis that visual information at a critical and functionally relevant time point following grasp contact supports variable and swift digit-based force control for dexterous object manipulation.NEW & NOTEWORTHY Humans excel in dexterous object manipulation by precisely coordinating grasp points and fingertip forces, highlighted in scenarios requiring countering object torques in advance, e.g., lifting a teacup without spilling will demand a unique digit force pattern based on the grip configuration at lift onset. Here, we show that visual information following grasp contact, a critical and functionally relevant time point, supports digit position variability and swift anticipatory force control to achieve a dexterous motor goal.

A Novel Passive Implantable Differential Mechanism to Restore Individuated Finger Flexion during Grasping following Tendon Transfer Surgery: A Pilot Study

Tendon transfer surgery is often used to restore hand grasp function following high median-ulnar nerve palsy. This surgery typically reroutes and sutures the tendon of the extensor carpi radialis longus (ECRL) muscle to all four flexor digitorum profundus (FDP) tendons of the hand, coupling them together. This makes it difficult to grasp irregularly shaped objects. We propose inserting a novel implantable passive device between the FDP tendons to surgically construct a differential mechanism, enabling the fingers to individually adapt to the irregular contours during grasping. These passive implants with no moving parts are fabricated from biocompatible materials. We tested the implants’ ability to create differential flexion between the index and middle fingers when actuated by a single muscle in two human cadaver hands using a computerized closed-loop control paradigm. In these cadaveric models, the implants enabled significantly more differential flexion between the index and middle fingers for a wide range of donor tendon tensions. The implants also redistributed fingertip forces between fingers. When grasping uneven objects, the difference in contact forces between fingers reduced by nearly 23% compared to the current suture-based surgery. These results suggest that self-adaptive grasp is possible in tendon transfers that drive multiple distal flexor tendons.

The Effect of Metacarpal Shortening on Finger Strength and Joint Motion: A Cadaveric Biomechanical Study

Discrepancies exist between previous biomechanical and clinical studies when determining acceptable metacarpal shortening after metacarpal fractures. This study aimed to determine the amount of acceptable shortening after a metacarpal fracture before finger motion and strength is compromised. We defrosted ten fresh-frozen cadaveric hands. A screw-driven external fixator was placed to stabilize the metacarpal, then a 15.0-mm section of the index metacarpal was excised and replaced with a three dimensional-printed, custom-designed polyethylene insert. The hand was then mounted on a custom testing rig, and the index finger was flexed using the flexor digitorum profundus tendon. Joint angles and fingertip force were recorded as the finger was flexed. Incrementally smaller inserts were placed, and testing was repeated. The average joint angles of the intact condition for the metacarpophalangeal, proximal interphalangeal, and distal interphalangeal joints were (54 [SD = 13], 79 [SD = 21], and 73 [SD = 10]), respectively. There were no statistically significant changes to any joint angle with any amount of shortening. The maximal fingertip contact pressures were 41 N (17), 31 N (12), 24 N (14), 19 N, (11), and 14 N (8) for the 15 mm, 12.5 mm, 10 mm, 7.5 mm, and 5 mm inserts, respectively. All changes in fingertip force by insert size were statistically significant. Metacarpal shortening does not affect flexion range of motion regardless of the amount of shortening, but it significantly affects finger strength. The loss of strength after shortening was approximately 6.5% per mm of shortening for the fractured metacarpal. When viewed in the context of the hand as a whole and the contribution of the index finger to grip being only 23.5%, it is unlikely that any shortening will significantly affect the average patient regarding grip strength. However, for a patient who requires fine motor strength, any amount of shortening may affect their finger function and needs to be addressed.

Asynchronous axonal firing patterns evoked via continuous subthreshold kilohertz stimulation

Objective. Transcutaneous electrical stimulation of peripheral nerves is a common technique to assist or rehabilitate impaired muscle activation. However, conventional stimulation paradigms activate nerve fibers synchronously with action potentials time-locked with stimulation pulses. Such synchronous activation limits fine control of muscle force due to synchronized force twitches. Accordingly, we developed a subthreshold high-frequency stimulation waveform with the goal of activating axons asynchronously. Approach. We evaluated our waveform experimentally and through model simulations. During the experiment, we delivered continuous subthreshold pulses at frequencies of 16.67, 12.5, or 10 kHz transcutaneously to the median and ulnar nerves. We obtained high-density electromyographic (EMG) signals and fingertip forces to quantify the axonal activation patterns. We used a conventional 30 Hz stimulation waveform and the associated voluntary muscle activation for comparison. We modeled stimulation of biophysically realistic myelinated mammalian axons using a simplified volume conductor model to solve for extracellular electric potentials. We compared the firing properties under kHz and conventional 30 Hz stimulation. Main results. EMG activity evoked by kHz stimulation showed high entropy values similar to voluntary EMG activity, indicating asynchronous axon firing activity. In contrast, we observed low entropy values in EMG evoked by conventional 30 Hz stimulation. The muscle forces evoked by kHz stimulation also showed more stable force profiles across repeated trials compared with 30 Hz stimulation. Our simulation results provide direct evidence of asynchronous firing patterns across a population of axons in response to kHz frequency stimulation, while 30 Hz stimulation elicited synchronized time-locked responses across the population. Significance. We demonstrate that the continuous subthreshold high-frequency stimulation waveform can elicit asynchronous axon firing patterns, which can lead to finer control of muscle forces.

Sensorimotor control of object manipulation following middle cerebral artery (MCA) stroke

Methods for assessing the loss of hand function post-stroke examine limited aspects of motor performance and are not sensitive to subtle changes that can cause deficits in everyday object manipulation tasks. Efficiently lifting an object entails a prediction of required forces based on intrinsic features of the object (sensorimotor integration), short-term updates in the forces required to lift objects that are poorly predicted (sensorimotor memory), as well as the ability to modulate distal fingertip forces, which are not measured by existing assessment tools used in clinics for both diagnostic and rehabilitative purposes. The presented research examined these three components of skilled object manipulation in 60 chronic, unilateral middle cerebral artery stroke participants. Performance was compared to age-matched control participants, and linear regressions were used to predict performance based on clinical scores. Most post-stroke participants performed below control levels in at least one of the tasks. Post-stroke participants presented with combinations of deficits in each of the tasks performed, regardless of the hemisphere damaged by the stroke. Surprisingly, the ability to modulate distal forces was impaired in those patients with damage ipsilateral (right hemisphere) to the hand being used. Sensorimotor integration was also impaired in patients with right hemisphere damage, though they performed at control levels in later lifts, whereas left-hemisphere-damaged patients did not. Lastly, during a task requiring sensorimotor memory, neither patient group performed outside of control ranges on initial lifts, with patients with right hemisphere damage showing impaired performance in later lifts suggesting they were unable to learn the mapping novel mapping of color and mass of the objects. The presented research demonstrates unilateral MCA stroke patients can have deficits in one or more components required for the successful manipulation of hand-held objects and that skillful object lifting requires intact bilateral systems. Further, this information may be used in future studies to aid efforts that target rehabilitation regimens to a stroke survivor's specific pattern of deficits.

An Anthropomorphic Robotic Finger With Innate Human-Finger-Like Biomechanical Advantages Part II: Flexible Tendon Sheath and Grasping Demonstration

The human hand has a fantastic ability to interact with various objects in the dynamic unstructured environment of our daily activities. We believe that this outstanding performance benefits a lot from the unique biological features of the hand musculoskeletal system. In Part I of this article, a bio-inspired anthropomorphic robotic finger was developed, based on which two human-finger-like biomechanical advantages were elaborately investigated, including the anisotropic variable stiffness associated with the ligamentous joints and the enlarged feasible force space associated with the reticular extensor mechanisms. In Part II, the fingertip force-velocity characteristics resulting from the flexible tendon sheath are studied. It indicates that the fingertip force–velocity workspace can be greatly augmented owing to the self-adaptive morphing of the flexible tendon sheaths, showing the average improvement of 41.2% theoretically and 117.5% experimentally compared with the results of 2 mm, 4 mm, and 6 mm size rigid tendon sheaths. Grasping tests and comparisons are then conducted with four three-fingered robotic hands (one with the robotic finger proposed in Part I, one with hinge joints, one with linear extensors, and one with rigid tendon sheaths) and the human hands of six subjects to handle various objects on flat, rough, and soft surfaces. The results show that the novel bio-inspired design in this research could improve the grasping success rates of the robotic hand. Compared with the grasping test results from the robotic hand with the bio-inspired robotic finger proposed in Part I, the overall grasping performance of a robotic hand with hinge joints, linear extensors, and rigid tendon sheaths decreases by 10%, 6%, and 17%, respectively. The results have also shown that with the embedded biomechanical advantages, even without complex control and sensory systems, the robotic fingers can achieve very comparable performance to human fingers in the grasping demonstrations presented, indicating average 94% of the success rate achieved by the human fingers. Successfully demonstrating 14 of 16 grasp types in the Cutkoskey taxonomy further shows the human-finger-like grasping capability of the proposed robotic fingers.

An Anthropomorphic Robotic Finger With Innate Human-Finger-Like Biomechanical Advantages Part I: Design, Ligamentous Joint, and Extensor Mechanism

Exploring human hand fundamental biomechanical features and exploiting them to robotic hands have been proven to be an effective approach to enhancing artificial hands' performance, especially when interacting with various objects in dynamic unstructured environments. In this article, a bioinspired anthropomorphic robotic finger is first proposed, which embeds human finger musculoskeletal features in the design. Based on this design, three human-finger-like biomechanical advantages are systematically investigated and embodied in the bioinspired robotic finger. This article for the first time derives, presents, and experimentally verifies the mathematical models for the variable stiffness of finger ligamentous joints and self-adaptive morphing mechanism of finger flexible tendon sheaths, and validates and compares the influence of the reticular and linear extensor morphologies on fingertip feasible forces in three-dimensional (3-D) space. In this Part I of the article, two of the biomechanical properties, i.e., joint stiffness generated by the ligamentous joint of the finger, and fingertip feasible force space influenced by the reticular extensor mechanism are systematically investigated through theoretical modeling and experimental verification. Correspondingly, two biomechanical advantages were found, i.e., the ligamentous joint of the finger could provide anisotropic variable joint stiffness, enhancing the adaptivity, dexterity, and stability of fingers; and a reticular extensor mechanism could enlarge the fingertip feasible force space in 3-D space by 30.9% theoretically and 146.4% experimentally on average compared with the linear extensor, contributing to enrich force conditions during interactions. The third biomechanical advantage, i.e., fingertip force–velocity workspace can be augmented through the flexible tendon sheath, and grasping tests for a robotic hand designed with the aforementioned advantages are presented in Part II of this article.

Evaluation of the FLEXotendon glove-III through a human subject case study.

Cervical spinal cord injury (SCI) can significantly impair an individual's hand functionality due to the disruption of nerve signals from the brain to the upper extremity. Robotic assistive hand exoskeletons have been proposed as a potential technology to facilitate improved patient rehabilitation outcomes, but few exoskeleton studies utilize standardized hand function tests and questionnaires to produce quantitative data regarding exoskeleton performance. This work presents the human subject case study evaluation of the FLEXotendon Glove-III, a 5 degree-of-freedom voice-controlled, tendon-driven soft robotic assistive hand exoskeleton for individuals with SCI. The exoskeleton system was evaluated in a case study with two individuals with SCI through two standardized hand function tests namely, the Jebsen-Taylor Hand Function Test and the Toronto Rehabilitation Institute Hand Function Test and three questionnaires (Capabilities of Upper Extremities Questionnaire, Orthotics Prosthetics Users Survey, Quebec User Evaluation of Satisfaction with Assistive Technology). Minor design changes were made to the exoskeleton: integrated fingertip force sensors to sense excessive grasp force, a quick connect system to expedite the exoskeleton glove swapping process between users, compact tendon tension sensors to measure tendon force for admittance control, and a redesigned smartphone app to encompass all aspects of exoskeleton use.

Inverse Saxophone-A Device to Study the Role of Individual Finger Perturbations on Grasp Stability.

The efficient coordination of fingertip forces to maintain static equilibrium while grasping an object continues to intrigue scientists. While many studies have explored this coordination, most of these studies assumed that interactions of hands primarily occur with rigid inanimate objects. Instead, our daily interactions with living and nonliving entities involve many dynamic, compliant, or fragile bodies. This paper investigates the fingertip force coordination on a manipulandum that changes its shape while grasping it. We designed a five-finger perturbation system with linear actuators at positions corresponding to each finger that would protrude outward from the center of the handle or retract toward the center of the handle as programmed. The behavior of the perturbed fingers and the other fingers while grasping this device was studied. Based on previous experiments on expanding and contracting handles, we hypothesized that each finger would exhibit a comparable response to similar horizontal perturbations. However, the response of the little finger was significantly different from the other fingers. We speculate that the central nervous system demonstrates preferential recruitment of some fingers over others while performing a task.

Action Classification of Sewing Operations based on Hands Posture and Fingertip Forces

Action Classification of Sewing Operations based on Hands Posture and Fingertip Forces

A Novel Soft Glove Utilizing Honeycomb Pneumatic Actuators (HPAs) for Assisting Activities of Daily Living.

Fabric-based pneumatic actuators (FPAs) are extensively employed in the design of lightweight and compliant soft wearable assistive gloves. However, conventional FPAs typically exhibit limited output force, thereby restricting the applications of such gloves. This paper presents the development of a novel honeycomb pneumatic actuator (HPA) constructed using flexible thermoplastic polyurethane (TPU) coating through hot pressing or ultrasonic welding techniques. Compared to the previously utilized double-layer fabric-based pneumatic actuators (DLFPAs), the HPAs yields a remarkable 862% increase in end output force. It can produce a tip force of 13.57 N at a pressure of 150 kPa. The integration of HPAs onto a soft pneumatic glove enables the facilitation of various activities of daily living. A series of trials involving nine patients were conducted to assess the effectiveness of the soft glove. The experimental results indicate that when assisted by the glove, the patients' finger metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints achieved angles of 87.67 ± 19.27° and 64.2 ± 30.66°, respectively. Additionally, the average fingertip force reached 10.16 ± 4.24 N, the average grip force reached 26.04 ± 15.08 N, and the completion rate of daily functions for the patients increased from 39% to 76%. These outcomes demonstrate that the soft glove effectively aids in finger movements and significantly enhances the patients' daily functioning.

Fingertip force estimation method of a human-like 3DOF robotic finger capable of fast tapping motion

Fingertip force estimation method of a human-like 3DOF robotic finger capable of fast tapping motion

Quantitative Identification of ADHD Tendency in Children With Immersive Fingertip Force Control Tasks.

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder that affects children. However, the traditional scale-based diagnosis methods rely more on subjective experiences, leading to a demand of objective biomarkers and quantified diagnostic methods. This study proposes a quantitative approach for identifying ADHD tendency based on fingertip pressing force control paradigm with immersive visual feedback. By extracting nine behavioral features from reaction time and dynamic force fluctuation features with high temporal and amplitude resolution, the proposed method can effectively capture the continuous changes in attention levels for ADHD diagnosis. The extracted features were analyzed using independent sample t-test and Pearson correlation to determine their association with ADHD-RS scale scores. Results showed that 12 statistical indicators were effective for distinguishing ADHD children from typically developed children, and several features of force control ability were also associated with core ADHD symptoms. A support vector machine (SVM) based classifier is trained for ADHD diagnosis and achieved an accuracy of 78.5%. This work provides an objective and quantitative approach for identifying ADHD tendency within a short testing time, and reveals the inherent correlation between the attention levels and the extracted features of reaction time and force fluctuation dynamics.

Design of Hyperextension Mechanism to Enhance Fingertip Force of Multi-Joint Linkage Mechanism Body-Powered Finger Prosthesis

Design of Hyperextension Mechanism to Enhance Fingertip Force of Multi-Joint Linkage Mechanism Body-Powered Finger Prosthesis

Effects of Feedback of Fingertip Force Information with Temporal Coded Vibration Stimulation on Precision Grasping Tasks

Tactile information plays an important role in human manipulation of objects; however, prosthetic limb placement or teleoperation requires the manipulation of alternative bodies in the absence of tactile sensations. To provide an alternative to tactile sensation, this study proposes and assesses a continuous feedback scheme with temporally coded vibration. This scheme was designed to provide discrete intended tactile information in response to changing object-controlled situations by repetitively presenting time-coded vibration patterns. The effects of the proposed scheme on an object with acatch-and-hold task in virtual reality were confirmed. Compared to the control feedback scheme that provides vibration only when the balance of the virtual grip force and object position is changed, the proposed feedback scheme has a better effect in terms of the success rate of holding on to the object with an appropriate holding force during the task. The effect is larger, especially in the invisible task condition, suggesting that the increased amount of information with coded vibration patterns can be used without any special training, especially without visual information. Considering the existing studies that show the effect of a feedback scheme in response to motion events, the continuous feedback scheme proposed in this study may be more suitable for movements that require sequential coordination and passive responses than stimulation methods based on motion events. This feedback scheme has potential applications not only in tele-technology but also in healthcare, such as rehabilitation.

Transfer of weight information depends differently on used hand and handedness for perception and action.

When lifting an object sequentially with the two hands, information about object weight can be transferred from one hand to the other. This information can be used to predictively scale fingertip forces and to form a perceptual estimation about the object's weight. This study investigated how weight information can be transferred between the two hands and how this depends on the used hand and handedness of the participant. Right- and left-handed participants lifted light and heavy objects with the right or left hand in a pseudorandomized order and estimated the object's weight. Results showed that predictive force scaling depended on the previously lifted object, with higher force rates if a previous object was heavy. This known effect of sensorimotor memory was mostly independent of the used hand and handedness, indicating that weight information could be transferred across hands for fingertip force scaling. Furthermore, a perceptual bias that depended on the previous lifted object was found, with lower weight estimations when the previous object was heavy compared to light. While this bias was found for both light and heavy objects in right-handers, it was only observed for light objects in left-handers. Notably, in contrast to the results on force scaling, this effect was not transferred across hands. These findings indicate that the transfer of weight information depends differently on the used hand and handedness for perceptual estimations and predictive force scaling.