Comparing clothing-mounted sensors with wearable sensors for movement analysis and activity classification

Inertial sensors are a useful instrument for long term monitoring in healthcare. In many cases, inertial sensor devices can be worn as an accessory or integrated into smart textiles. In some situations, it may be beneficial to have data from multiple inertial sensors, rather than relying on a single worn sensor, since this may increase the accuracy of the analysis and better tolerate sensor errors. Integrating multiple sensors into clothing improves the feasibility and practicality of wearing multiple devices every day, in approximately the same location, with less likelihood of incorrect sensor orientation. To facilitate this, the current work investigates the consequences of attaching lightweight sensors to loose clothes. The intention of this paper is to discuss how data from these clothing sensors compare with similarly placed body worn sensors, with additional consideration of the resulting effects on activity recognition. This study compares the similarity between the two signals (body worn and clothing), collected from three different clothing types (slacks, pencil skirt and loose frock), across multiple daily activities (walking, running, sitting, and riding a bus) by calculating correlation coefficients for each sensor pair. Even though the two data streams are clearly different from each other, the results indicate that there is good potential of achieving high classification accuracy when using inertial sensors in clothing

Modelling of surface identifying characteristics using Fourier series

Texture and small-scale surface details are widely recognised as playing an important role in the haptic identification of objects. In order to simulate realistic textures in haptic virtual environments, it has become increasingly necessary to identify a robust technique for modelling of surface profiles. This paper describes a method whereby Fourier series spectral analysis is employed in order to describe the measured surface profiles of several characteristic surfaces. The results presented suggest that a bandlimited Fourier series can be used to provide a realistic approximation to surface amplitude profiles

Current over-stressing small DC motors to evaluate performance limits of electromechanical actuators for haptic applications

Actuators for haptic devices tend to have a different set of requirements in comparison to many other engineering applications. Small permanent magnet DC electric motors are commonly used as actuators in haptic devices and, in operation, tend to spend a significant period of time in a `stalled' condition where they are attempting to oppose an applied force. Ideally a haptic actuator together with its power amplifier exchange energy reversibly with the mechanical loads. However this is not feasible at room temperature and to achieve good force performance results in energy loss as heat in the motor windings. This paper identifies the relationship between heat loss and force generation in haptic electromagnetic actuators. The work then presents results on current over-stressing of small DC motors so as to understand the risks of demagnetisation against thermal damage to the armature. Results indicate that it should be possible to apply short current over-stresses to commercial DC permanent magnet motors to increase end point force. Also by paying careful attention to heat dissipation in the design of small permanent magnet actuators motors, it should be possible to improve the overall performance of actuators for haptic applications

A smoothed particle hydrodynamics algorithm for haptic rendering of dental filling materials

Using haptic interfaces to assist the training of skills within the curriculum of undergraduate dentists provides a unique opportunity to advance rendering algorithms and engineering of haptic devices. In this paper we use the dental context to explore a rendering technique called smoothed particle hydrodynamics (SPH) as a potential method to train students on appropriate techniques for insertion of filling material into a previously prepared (virtual) dental cavity. The paper also considers how problems of haptic rendering might be implemented on a Graphical Processing Unit (GPU) that operates in the haptics control loop. The filling simulation used 3000 particles to represent the cavity boundary (approx. 1400 particles), tool (approx. 42 particles) and filling material (approx. 1600 particles), running at an average of 447Hz. Novel smoothing function in SPH was developed and its flexibility is presented

Modelling the air-gap field strength of electric machines to improve performance of haptic mechanisms

The air-gap of electro-magnetic (EM) actuators determines key operating parameters such as their ability to generate force. In haptic devices these parameters are not optimised for the conditions typically seen in operation and include the heat produced in the air-gap, the volume of the air-gap, and the intensity and direction of the magnetic field. The relationship between these parameters is complex thus design decisions are difficult to make. This paper considers the role of the radial magnetic field in cylindrical electric motors, a type often used in haptic devices. Two models are derived and compared with experimental measurements. The first model is a closed form solution, the second is a classic Poisson solution to Ampere's equation. These models are shown to be valid for making more general design decisions in relation to haptic actuators, and in particular allow an evaluation of the trade off between the volume of the air-gap, the resulting radial magnetic field and hence heat generated and the resulting forces

Development of a wearable assistive soft robotic device for elbow rehabilitation

The loss of motor function at the elbow joint can result as a consequence of stroke. Stroke is a clinical illness resulting in long lasting neurological deficits often affecting somatosensory and motor cortices. More than half of those that recover from a stroke survive with disability in their upper arm and need rehabilitation therapy to help in regaining functions of daily living. In this paper, we demonstrated a prototype of a low-cost, ultra-light and wearable soft robotic assistive device that could aid administration of elbow motion therapies to stroke patients. In order to assist the rotation of the elbow joint, the soft modules which consist of soft wedge-like cellular units was inflated by air to produce torque at the elbow joint. Highly compliant rotation can be naturally realised by the elastic property of soft silicone and pneumatic control of air. Based on the direct visual-actuation control, a higher control loop utilised visual processing to apply positional control, the lower control loop was implemented by an electronic circuit to achieve the desired pressure of the soft modules by Pulse Width Modulation. To examine the functionality of the proposed soft modular system, we used an anatomical model of the upper limb and performed the experiments with healthy participants

Comparing loose clothing-mounted sensors with body-mounted sensors in the analysis of walking

A person’s walking pattern can reveal important information about their health. Mounting multiple sensors onto loose clothing potentially offers a comfortable way of collecting data about walking and other human movement. This research investigates how well the data from three sensors mounted on the lateral side of clothing (on a pair of trousers near the waist, upper thigh and lower shank) correlate with the data from sensors mounted on the frontal side of the body. Data collected from three participants (two male, one female) for two days were analysed. Gait cycles were extracted based on features in the lower-shank accelerometry and analysed in terms of sensor-to-vertical angles (SVA). The correlations in SVA between the clothing- and body-mounted sensor pairs were analysed. Correlation coefficients above 0.76 were found for the waist sensor pairs, while the thigh and lower-shank sensor pairs had correlations above 0.90. The cyclical nature of gait cycles was evident in the clothing data, and it was possible to distinguish the stance and swing phases of walking based on features in the clothing data. Furthermore, simultaneously recording data from the waist, thigh, and shank was helpful in capturing the movement of the whole leg

Novel instrumented frame for standing exercising of users with complete spinal cord injuries

This paper describes a Functional Electrical Stimulation (FES) standing system for rehabilitation of bone mineral density (BMD) in people with Spinal Cord Injury (SCI). BMD recovery offers an increased quality of life for people with SCI by reducing their risk of fractures. The standing system developed comprises an instrumented frame equipped with force plates and load cells, a motion capture system, and a purpose built 16-channel FES unit. This system can simultaneously record and process a wide range of biomechanical data to produce muscle stimulation which enables users with SCI to safely stand and exercise. An exergame provides visual feedback to the user to assist with upper-body posture control during exercising. To validate the system an alternate weight-shift exercise was used; 3 participants with complete SCI exercised in the system for 1 hour twice-weekly for 6 months. We observed ground reaction forces over 70% of the full body-weight distributed to the supporting leg at each exercising cycle. Exercise performance improved for each participant by an increase of 13.88 percentage points of body-weight in the loading of the supporting leg during the six-month period. Importantly, the observed ground reaction forces are of higher magnitude than other studies which reported positive effects on BMD. This novel instrumentation aims to investigate weight bearing standing therapies aimed at determining the biomechanics of lower limb joint force actions and postural kinematics

Analysis of EEG signal to detect motor command generation towards stroke rehabilitation

Our aim is to reconstruct the brain-body loop of stroke patients via an EEG-driven robotic system. After the detection of motor command generation, the robotic arm should assist patient’s movement at the correct moment and in a natural way. In this study we performed EEG measurements from healthy subjects performing discrete spontaneous motion. An EEG analysis based on the temporal correlation of the brain activity was employed to determine the onset of single motion motor command generation

A feasible study of EEG-driven assistive robotic system for stroke rehabilitation

Stroke is a medical emergency and can cause a neurological damage, affecting the motor and sensory systems. Harnessing brain plasticity should make it possible to reconstruct the closed loop between the brain and the body, i.e., association of the generation of the motor command with the somatic sensory feedback might enhance motor recovery. In order to aid reconstruction of this loop with a robotic device it is necessary to assist the paretic side of the body at the right moment to achieve simultaneity between motor command and feedback signal to somatic sensory area in brain. To this end, we propose an integrated EEG-driven assistive robotic system for stroke rehabilitation. Depending on the level of motor recovery, it is important to provide adequate stimulation for upper limb motion. Thus, we propose an assist arm incorporating a Magnetic Levitation Joint that can generate a compliant motion due to its levitation and mechanical redundancy. This paper reports on a feasibility study carried out to verify the validity of the robot sensing and on EEG measurements conducted with healthy volunteers while performing a spontaneous arm flexion/extension movement. A characteristic feature was found in the temporal evolution of EEG signal in the single motion prior to executed motion which can aid in coordinating timing of the robotic arm assistance onset