Publications
384 results found
Takagi A, Gomi H, Burdet E, et al., 2022, A model predictive control strategy to regulate movements and interactions
<jats:title>Abstract</jats:title><jats:p>Humans are adept at moving the arm to interact with objects and surfaces. The brain is thought to regulate motion and interactions using two different controllers, one specialized for movements and the other for force regulation. However, it remains unclear whether different control mechanisms are necessary. Here we show that the brain can employ a single high-level control strategy for both movement and interaction control. The Model Predictive Control (MPC) strategy introduced in this paper uses an internal model of the environment to plan the arm’s muscle activity whilst updating its predictions using periodic feedback. Computer simulations demonstrate MPC’s ability to produce human-like movements and after-effects in free and force field environments. It can simultaneously regulate both force and stiffness during interactions, and can accomplish motor tasks demanding transitions between motion and interaction control. Model Predictive Control promises to be an important tool to test ideas of motor control as it can handle nonlinear dynamics with changing environments and goals without having to specify the movement duration.</jats:p>
Li Y, Sena A, Wang Z, et al., 2022, A review on interaction control for contact robots through intent detection, Progress in Biomedical Engineering, Vol: 4, Pages: 1-21, ISSN: 2516-1091
Interaction control presents opportunities for contact robots physically interacting with their human user, such as assistance targeted to each human user, communication of goals to enable effective teamwork, and task-directed motion resistance in physical training and rehabilitation contexts. Here we review the burgeoning field of interaction control in the control theory and machine learning communities, by analysing the exchange of haptic information between the robot and its human user, and how they share the task effort. We first review the estimation and learning methods to predict the human user intent with the large uncertainty, variability and noise and limited observation of human motion. Based on this motion intent core, typical interaction control strategies are described using a homotopy of shared control parameters. Recent methods of haptic communication and game theory are then presented to consider the co-adaptation of human and robot control and yield versatile interactive control as observed between humans. Finally, the limitations of the presented state of the art are discussed and directions for future research are outlined.
Huang Y, Eden J, Ivanova E, et al., 2022, Human Performance of Three Hands in Unimanual, Bimanual and Trimanual Tasks., Annu Int Conf IEEE Eng Med Biol Soc, Vol: 2022, Pages: 1493-1497
Trimanual operation using a robotic supernumerary limb is a new and challenging mechanism for human operators that could enable a single user to perform tasks requiring more than two hands. Foot-controlled interfaces have previously proven able to be intuitively controlled, enabling simple tasks to be performed. However, the effect of going from unimanual to bimanual and then to trimanual tasks on subjects performance and coordination is not well understood. In this paper, unimanual, bimanual and trimanual teleoperation tasks were performed in a virtual reality scene to evaluate the impact of extending to trimanual actions. 15 participants were required to move their limbs together in a coordinated reaching activity. The results show that the addition of another hand resulted in an increase in operating time, where the time increased in going from unimanual to bimanual operation and then increased further when going from bimanual to trimanual. Moreover, the success rate for performing bimanual and trimanual tasks was strongly influenced by the subject's performance in ipsilateral hand-foot activities, where the ipsilateral combination had a lower success rate than contralateral limbs. The addition of a hand did not affect any two-hand coordination rate and even in some cases reduced coordination deviations. Clinical relevance - This work can contribute to build efficient training and learning framework on human multiple limbs motion control and coordination for both rehabilitation and augmentation.
Farkhatdinov I, Garnier A, Arichi T, et al., 2022, Evaluation of a Portable fMRI Compatible Robotic Wrist Interface., Annu Int Conf IEEE Eng Med Biol Soc, Vol: 2022, Pages: 2535-2539
This paper presents evaluation of a portable fMRI compatible haptic interface to study the brain correlates of sensorimotor control during wrist motion. The interface is actuated by a shielded DC motor located more than 2 m away from the 3T MR scanner's bore. The achievable wrist torque of the interface is up to 2 Nm, and the interface provides sufficient bandwidth for human motor control experiments. Ergonomic and fMRI compatibility testing with a 3T MR scanner showed that the interface is MR safe, compatible with a strong static magnetic field and radio frequency emission, and its operation does not affect the quality of the acquired images. Clinical Relevance- We present and evaluate an fMRI compatible robotic interface to study human wrist joint motor function.
Perez NP, Eden J, Burdet E, et al., 2022, Lateralization of Impedance Control in Dynamic Versus Static Bimanual Tasks., Annu Int Conf IEEE Eng Med Biol Soc, Vol: 2022, Pages: 785-789
In activities of daily living that require bimanual coordination, humans often assign a role to each hand. How do task requirements affect this role assignment? To address this question, we investigated how healthy right-handed participants bimanually manipulated a static or dynamic virtual object using wrist flexion/extension while receiving haptic feedback through the interacting object's torque. On selected trials, the object shook strongly to destabilize the bimanual grip. Our results show that participants reacted to the shaking by increasing their wrist co-contraction. Unlike in previous work, handedness was not the determining factor in choosing which wrist to co-contract to stabilize the object. However, each participant preferred to co-contract one hand over the other, a choice that was consistent for both the static and dynamic objects. While role allocation did not seem to be affected by task requirements, it may have resulted in different motor behaviours as indicated by the changes in the object torque. Further investigation is needed to elucidate the factors that determine the preference in stabilizing with either the dominant or non-dominant hand.
Perez NP, Eden J, Ivanova E, et al., 2022, Is a Robot Needed to Modify Human Effort in Bimanual Tracking?, IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 7, Pages: 8069-8075, ISSN: 2377-3766
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- Citations: 2
Bracklein M, Barsakcioglu DY, Ibanez J, et al., 2022, The control and training of single motor units in isometric tasks are constrained by a common input signal, ELIFE, Vol: 11, ISSN: 2050-084X
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- Citations: 8
Dall'Orso S, Arichi T, Fitzgibbon SP, et al., 2022, Development of functional organization within the sensorimotor network across the perinatal period, HUMAN BRAIN MAPPING, Vol: 43, Pages: 2249-2261, ISSN: 1065-9471
Huang Y, Ivanova E, Eden J, et al., 2022, Identification of Multiple Limbs Coordination Strategies in a Three-Goal Independent Task, IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS, Vol: 4, Pages: 348-351
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- Citations: 2
Murali PK, Dutta A, Gentner M, et al., 2022, Active Visuo-Tactile Interactive Robotic Perception for Accurate Object Pose Estimation in Dense Clutter, IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 7, Pages: 4686-4693, ISSN: 2377-3766
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- Citations: 3
Shushtari M, Takagi A, Lee J, et al., 2022, Balance strategy in hoverboard control., Scientific Reports, Vol: 12, Pages: 1-11, ISSN: 2045-2322
This study examines how people learn to perform lower limb control in a novel task with a hoverboard requiring to maintain dynamic balance. We designed an experiment to investigate the learning of hoverboard balance and two control strategies: A hip strategy, which mainly uses hip movements to change the angle of the foot, and an ankle strategy relying more on ankle motion to control the orientation of hoverboard plates controlling the motion. Motor learning was indicated by a significant [Formula: see text]% decrease in the trial completion time (p < 0.001) and a significant 24 ± 11% decrease in total muscle activation (p < 0.001). Furthermore, the participants, who had no prior experience riding a hoverboard, learned an ankle strategy to maintain their balance and control the hoverboard. This is supported by significantly stronger cross-correlation, phase synchrony, lower dynamic time warping distance between the hoverboard plate orientation controlling hoverboard motion, and the ankle angle when compared to the hip angle. The adopted ankle strategy was found to be robust to the foot orientation despite salient changes in muscle group activation patterns. Comparison with results of an experienced hoverboard rider confirmed that the first-time riders adopted an ankle strategy.
Eden J, Bräcklein M, Ibáñez J, et al., 2022, Principles of human movement augmentation and the challenges in making it a reality, Nature Communications, Vol: 13, ISSN: 2041-1723
Augmenting the body with artificial limbs controlled concurrently to one's natural limbs has long appeared in science fiction, but recent technological and neuroscientific advances have begun to make this possible. By allowing individuals to achieve otherwise impossible actions, movement augmentation could revolutionize medical and industrial applications and profoundly change the way humans interact with the environment. Here, we construct a movement augmentation taxonomy through what is augmented and how it is achieved. With this framework, we analyze augmentation that extends the number of degrees-of-freedom, discuss critical features of effective augmentation such as physiological control signals, sensory feedback and learning as well as application scenarios, and propose a vision for the field.
Mace M, Mutalib SA, Ogrinc M, et al., 2022, GripAble: an accurate, sensitive and robust digital device for measuring grip strength, Journal of Rehabilitation and Assistive Technologies Engineering, Vol: 9, Pages: 1-12, ISSN: 2055-6683
Introduction: Grip strength is a reliable biomarker of overall health and physiological well-being. It is widely used in clinical practice as an outcome measure. This paper demonstrates the measurement characteristics of GripAble, a wireless mobile handgrip device that measures grip force both isometrically and elastically-resisted for assessment and training of hand function. Methods: A series of bench tests were performed to evaluate GripAble's grip force measurement accuracy and sensitivity. Measurement robustness was evaluated through repeated drop tests interwoven with error verification test phases. Results: GripAble's absolute measurement error at the central position was under 0.81 and 1.67 kg (95th percentiles; N = 47) when measuring elastically and isometrically, respectively, providing similar or better accuracy than the industry-standard Jamar device. Sensitivity was measured as 0.062 ± 0.015 kg (mean ± std; 95th percentiles: [0.036, 0.089] kg; N = 47), independent of the applied force. There was no significant performance degradation following impact from 30 drops from a height >1.5 m. Conclusion: GripAble is an accurate and reliable grip strength dynamometer. It is highly sensitive and robust, which in combination with other novel features (e.g. portability, telerehabilitation and digital data tracking) enable broad applicability in a range of clinical caseloads and environments.
Mutalib SA, Mace M, Seager C, et al., 2022, Modernising grip dynamometry: Inter-instrument reliability between GripAble and Jamar, BMC Musculoskeletal Disorders, Vol: 23, ISSN: 1471-2474
Introduction:Maximum grip strength (MGS) is a reliable biomarker of overall health and physiological well-being. Therefore, an accurate and reliable measurement device is vital for ensuring the validity of the MGS assessment. This paper presents GripAble, a mobile hand grip device for the assessment of MGS. GripAble’s performance was evaluated using an inter-instrument reliability test against the widely used Jamar PLUS+ dynamometer.Methods:MGS data from sixty-three participants (N = 63, median (IQR) age = 29.0 (29.5) years, 33 M/30 F) from both hands using GripAble and Jamar PLUS+ were collected and compared. Intraclass correlation (ICC), regression, and Bland and Altman analysis were performed to evaluate the inter-instrument reliability and relationship in MGS measurements between GripAble and Jamar PLUS+ .Results:GripAble demonstrates good-to-excellent inter-instrument reliability to the Jamar PLUS+ with ICC3,1 = 0.906 (95% CI [0.87—0.94]). GripAble’s MGS measurement is equivalent to 69% (95% CI [0.67—0.71]%) of Jamar PLUS+’s measurement. There is a proportional difference in mean MGS between the two devices, with the difference in MGS between GripAble and Jamar PLUS+ increasing with MGS.Conclusion:The GripAble is a reliable tool for measuring grip strength. However, the MGS readings from GripAble and Jamar PLUS+ should not be interchanged for serial measurements of the same patient, nor be translated directly from one device to the other. A new normative MGS data using GripAble will be collected and accessed through the software for immediate comparison to age and gender-matched subpopulations.
Fourie C, Figueroa N, Shah J, et al., 2022, Joint Action, Adaptation, and Entrainment in Human-Robot Interaction, 17th Annual ACM/IEEE International Conference on Human-Robot Interaction (HRI), Publisher: ASSOC COMPUTING MACHINERY, Pages: 1250-1253, ISSN: 2167-2121
Yu H, Sena A, Burdet E, 2022, A wearable system with harmonic oscillations to assess finger biomechanics, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Publisher: IEEE, Pages: 11150-11157, ISSN: 2153-0858
Perez NP, Eden J, Ivanova E, et al., 2022, Is a robot needed to modify human effort in bimanual tracking?, 9th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), Publisher: IEEE, ISSN: 2155-1782
Allemang-Trivalle A, Eden J, Huang Y, et al., 2022, Comparison of human trimanual performance between independent and dependent multiple-limb training modes, 9th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), Publisher: IEEE, ISSN: 2155-1782
Moorthy V, Kassanos P, Burdet E, et al., 2022, Stencil Printing of Low-Cost Carbon-Based Stretchable Strain Sensors, IEEE Sensors Conference, Publisher: IEEE, ISSN: 1930-0395
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- Citations: 1
Allemang-Trivalle A, Eden J, Ivanova E, et al., 2022, How long does it take to learn trimanual coordination?, 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) - Social, Asocial, and Antisocial Robots, Publisher: IEEE, Pages: 211-216
Li R, Li Y, Li SE, et al., 2021, Indirect Shared Control for Cooperative Driving Between Driver and Automation in Steer-by-Wire Vehicles, IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, Vol: 22, Pages: 7826-7836, ISSN: 1524-9050
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- Citations: 19
Carboni G, Nanayakkara T, Takagi A, et al., 2021, Adapting the visuo-haptic perception through muscle coactivation, SCIENTIFIC REPORTS, Vol: 11, ISSN: 2045-2322
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- Citations: 4
Broderick M, Almedom L, Burdet E, et al., 2021, Self-Directed Exergaming for Stroke Upper Limb Impairment Increases Exercise Dose Compared to Standard Care, NEUROREHABILITATION AND NEURAL REPAIR, Vol: 35, Pages: 974-985, ISSN: 1545-9683
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- Citations: 5
Lee S-H, Hwang Y-J, Lee H-J, et al., 2021, Proof-of-Concept of a Sensor-Based Evaluation Method for Better Sensitivity of Upper-Extremity Motor Function Assessment, SENSORS, Vol: 21
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- Citations: 7
Qian K, Arichi T, Price A, et al., 2021, An eye tracking based virtual reality system for use inside magnetic resonance imaging systems, Scientific Reports, Vol: 11, Pages: 1-17, ISSN: 2045-2322
Patients undergoing Magnetic Resonance Imaging (MRI) often experience anxiety and sometimes distress prior to and during scanning. Here a full MRI compatible virtual reality (VR) system is described and tested with the aim of creating a radically different experience. Potential benefits could accrue from the strong sense of immersion that can be created with VR, which could create sense experiences designed to avoid the perception of being enclosed and could also provide new modes of diversion and interaction that could make even lengthy MRI examinations much less challenging. Most current VR systems rely on head mounted displays combined with head motion tracking to achieve and maintain a visceral sense of a tangible virtual world, but this technology and approach encourages physical motion, which would be unacceptable and could be physically incompatible for MRI. The proposed VR system uses gaze tracking to control and interact with a virtual world. MRI compatible cameras are used to allow real time eye tracking and robust gaze tracking is achieved through an adaptive calibration strategy in which each successive VR interaction initiated by the subject updates the gaze estimation model. A dedicated VR framework has been developed including a rich virtual world and gaze-controlled game content. To aid in achieving immersive experiences physical sensations, including noise, vibration and proprioception associated with patient table movements, have been made congruent with the presented virtual scene. A live video link allows subject-carer interaction, projecting a supportive presence into the virtual world.
Bräcklein M, Ibáñez J, Barsakcioglu DY, et al., 2021, The control and training of single motor units in isometric tasks are constrained by a common synaptic input signal
<jats:title>Abstract</jats:title><jats:p>Recent developments in neural interfaces enable the real-time and non-invasive tracking of motor neuron spiking activity. Such novel interfaces provide a promising basis for human motor augmentation by extracting potential high-dimensional control signals directly from the human nervous system. However, it is unclear how flexibly humans can control the activity of individual motor neurones to effectively increase the number of degrees-of-freedom available to coordinate multiple effectors simultaneously. Here, we provided human subjects (N=7) with real-time feedback on the discharge patterns of pairs of motor units (MUs) innervating a single muscle (tibialis anterior) and encouraged them to independently control the MUs by tracking targets in a 2D space. Subjects learned control strategies to achieve the target-tracking task for various combinations of MUs. These strategies rarely corresponded to a volitional control of independent input signals to individual MUs. Conversely, MU activation was consistent with a common input to the MU pair, while individual activation of the MUs in the pair was predominantly achieved by alterations in de-recruitment order that could be explained with history-dependent changes in motor neuron excitability. These results suggest that flexible MU control based on independent synaptic inputs to single MUs is not a simple to learn control strategy.</jats:p>
Takagi A, Li Y, Burdet E, 2021, Flexible Assimilation of Human's Target for Versatile Human-Robot Physical Interaction, IEEE TRANSACTIONS ON HAPTICS, Vol: 14, Pages: 421-431, ISSN: 1939-1412
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- Citations: 3
Budhota A, Chua KSG, Hussain A, et al., 2021, Robotic assisted upper limb training post stroke: a randomized control trial using combinatory approach toward reducing workforce demands, Frontiers in Neurology, Vol: 12, ISSN: 1664-2295
Post stroke upper limb rehabilitation is a challenging problem with poor outcomes as 40% of survivors have functionally useless upper limbs. Robot-aided therapy (RAT) is a potential method to alleviate the effort of intensive, task-specific, repetitive upper limb exercises for both patients and therapists. The present study aims to investigate how a time matched combinatory training scheme that incorporates conventional and RAT, using H-Man, compares with conventional training toward reducing workforce demands. In a randomized control trial (NCT02188628, www.clinicaltrials.gov), 44 subacute to chronic stroke survivors with first-ever clinical stroke and predominant arm motor function deficits were recruited and randomized into two groups of 22 subjects: Robotic Therapy (RT) and Conventional Therapy (CT). Both groups received 18 sessions of 90 min; three sessions per week over 6 weeks. In each session, participants of the CT group received 90 min of 1:1 therapist-supervised conventional therapy while participants of the RT group underwent combinatory training which consisted of 60 min of minimally-supervised H-Man therapy followed by 30 min of conventional therapy. The clinical outcomes [Fugl-Meyer (FMA), Action Research Arm Test and, Grip Strength] and the quantitative measures (smoothness, time efficiency, and task error, derived from two robotic assessment tasks) were independently evaluated prior to therapy intervention (week 0), at mid-training (week 3), at the end of training (week 6), and post therapy (week 12 and 24). Significant differences within group were observed at the end of training for all clinical scales compared with baseline [mean and standard deviation of FMA score changes between baseline and week 6; RT: Δ4.41 (3.46) and CT: Δ3.0 (4.0); p < 0.01]. FMA gains were retained 18 weeks post-training [week 24; RT: Δ5.38 (4.67) and week 24 CT: Δ4.50 (5.35); p < 0.01]. The RT group clinical scores improved similarly when com
Berret B, Conessa A, Schweighofer N, et al., 2021, Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision, PLOS COMPUTATIONAL BIOLOGY, Vol: 17, ISSN: 1553-734X
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- Citations: 13
Ivanova E, Eden J, Zhu S, et al., 2021, Short time delay does not hinder haptic communication benefits, IEEE Transactions on Haptics, Vol: 14, Pages: 322-327, ISSN: 1939-1412
Haptic communication, the exchange of force and tactile information during dancing or moving a table together, has been shown to benefit the performance of human partners. Similarly, it could also be used to improve the performance of robots working in contact with a human operator. As we move to more robot integrated workspaces, how common network features such as delay or jitter impact haptic communication need to be better understood. Here using a human-like interactive robotic controller, that has been found to be indistinguishable by humans to human interaction, we evaluate how subjects’ performance and perception is altered by varying levels of transmission delay. We find that subjects are able to recognise haptic delay at very small levels within haptic interaction. However, while they are consciously aware of the delay they can only compensate for it up until a certain point, after which they perceive it as the addition of noise/impedance into the system.
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