G.B.), m.ghajari@imperial.ac.uk (M.G.), r.hewson@imperial.ac.uk (R.H.), A.Alazmani@leeds.ac.uk (A.A.), P.R.Culmer@leeds.ac.uk (P.C.). AbstractTactile sensors are essential for robotic systems to interact safely and effectively with the external world, they also play a vital role in some smart healthcare systems. Despite advances in areas including materials/composites, electronics and fabrication techniques, it remains challenging to develop low cost, high performance, durable, robust, soft tactile sensors for realworld applications. This paper presents the first Soft Inductive Tactile Sensor (SITS) which exploits an inductance-transducer mechanism based on the eddy-current effect. SITSs measure the inductance variation caused by changes in AC magnetic field coupling between coils and conductive films. Design methodologies for SITSs are discussed by drawing on the underlying physics and computational models, which are used to develop a range of SITS prototypes. An exemplar prototype achieves a state-of-the-art resolution of 0.82 mN with a measurement range over 15 N. Further tests demonstrate that SITSs have low hysteresis, good repeatability, wide bandwidth, and an ability to operate in harsh environments. Moreover, they can be readily fabricated in a durable form and their design is inherently extensible as highlighted by a 4x4 SITS array prototype. These outcomes show the potential of SITS systems to further advance tactile sensing solutions for integration into demanding real-world applications.

iPAM is a dual robotic system currently being developed in the UK under a NHS New and Emerging Applications of Technologies (NEAT) grant. The aim of the system is to provide assistive upper-limb therapeutic excercise for post-stroke rehabilitation. iPAM features two co-ordinated, pneumatically-actuated robotic arms which attach to the patient's forearm and upper-arm to provide assistance, mimicking the intervention of a physiotherapist. The system design and manufacture has been completed and the robot installed at a local hospital (St Mary's, Leeds PCT, UK) inside a community rehabilitation unit. The controller is currently developed and 'tuned' to provide gravity compensation for robots, removing any potentially damaging loads on the patient arm. The control scheme has been tested in simulation and using a mechanical arm model to ensure safe operation.Two small scale trials have been conducted to assess two facets of the robot design; firstly the mechanical design of the system to unimpede normal arm movement and secondly, its ability to provide varying levels of lift to the patient's arm to increase range of movement. The former of these trials compares free arm movement in healthy volunteers and Stroke patients with that when attached to iPAM. The robot was configured to compensate for its own weight, so the human upper-limb was unloaded. It was found that the robot had no significant affect on movement patterns. The second group of patient trials evaluated the operation of various levels of assistance against gravity. Patients were asked to point to a target with varying degrees of 'lift' applied to their upper and lower arm. In those patients with significant upper-limb impairment it was found that higher values of 'lift' improved the extent of reach but altered the movement pattern. Results from the trials demonstrated the suitability of certain modes of operation depending on the severity of patient disability.

Abstract-This paper investigates the effect of maximum indentation force and depth on people's ability to accurately discriminate compliance using indirect visual information only. Participants took part in two psychophysical experiments in which they were asked to choose the 'softest' sample out of a series of presented sample pairs. In the experiments, participants observed a computer-actuated tip indent the sample pairs to one of two conditions; maximum depth (10mm) or maximum force (4N). This indentation process simulates tool operated palpation in laparoscopic surgery. Results were used to plot psychometric functions as a measure of accuracy of compliance discriminability. A comparison indicated that participants performed best in the task where they judged samples being indented to a pre-set maximum force relying solely on visual cues, which demonstrates the effect of visual information on compliance discrimination. Results also show that indentation cues such as force and deformation depth have different effects on our ability to visually discriminate compliance. These findings will inform future work on designing a haptic feedback system capable of augmenting visual and haptic information independently for optimal compliance discrimination performance.

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