Virtual reality allows users to immerse themselves into an alternate reality. Science fiction books and films, like Ready Player One, have represented the interaction with virtual reality as a body and mind immersion, where the user is able to move freely, interact with objects and feel the surrounding environment like in the real world. Although we are not there yet, advances in technology are bringing us closer to this vision. One of which, is the advancement in dielectric elastomers sensors (DES). By integrating DES into a wetsuit to capture shoulder and elbow motion, we are able to replicate the movement in a virtual reality humanoid avatar. Compared to the elbow motion, which can be modelled as extension and flexion motions, the shoulder joint is much more complex with a greater number of degrees of freedom. In this paper we present a wetsuit with 5 dielectric elastomer sensors that captures the elbow flexion/extension, shoulder flexion/extension, abduction/adduction and rotation with an RMSE of 11.8°, 5.2°, 5.4° and 7.9° respectively.
The superior swimming ability of fish has encouraged the development of fish-like robots. To fully capture fish swimming kinematics a continuum under-actuated robot can be used, and there are many examples of such robots in the literature. But for realistic fish-like swimming in strong currents such robots will benefit from closed-loop feedback. We demonstrate how this can be achieved, underwater, using a stretchy neoprene sensing skin with embedded, discrete dielectric elastomer stretch sensors. The latest prototype skin, with 8 sensors, 4 on each side, is currently being evaluated on an underactuated tensegrity fish-like robot driven by a stepper motor. Carangiform movement of the body has been characterized using cameras and this data has been compared with a virtual model of the robot that uses sensor input for real-time model kinematic data. Four angles along the body defined the shape. A root mean square error between model and true camera angles of less than 3° was calculated for realistic cangiform motion at 0.5 Hz tail frequency.
Hand gesture recognition algorithms require information from the material world to be converted to digital data. In this paper we present an analysis of dielectric elastomer sensors for hand gesture recognition. A glove with five dielectric elastomer sensors has been used to collect motion data from the hand. The capacitance value of each sensor was read and analysed for a total of 24 participants. The study shows that the sensors provide enough information to differentiate gestures from each participant, although the maximum capacitance value varied with each participant, making gesture recognition over all participants difficult. Data processing allowed for this problem to be solved.
Accurately capturing human motion underwater has potential applications in diver health monitoring, human- machine interaction and performance sport coaching. Unfortunately the human body has approximately 200 bones and 600 skeletal muscles giving rise to a broad range of degrees of freedom. To effectively capture this movement with dielectric elastomer sensors a substantial network is required. One often overlooked challenge is the connection between the dielectric elastomer sensor and central electronics. On land this is as simple as wires connecting the two. Underwater however, especially when considering a network of sensors, this becomes a more complicated task.
In the proposed method parallel plate capacitors are used to transfer power across the encapsulation layer to the sensor, removing any need for protruding wires or cable glands. With one electrode placed within the encapsulation and the second connected to the sensor, sensors are replaceable even underwater. To maintain sensor performance however, a relatively high capacitance is required. For example if the coupling capacitance is 20x greater than sensor capacitance, sensitivity is reduce by approximately 20%. Whereas if the coupling capacitance is only 10x greater, sensitivity is reduced by 40%. Due to these high capacitance requirements combined with the area and weight restrictions of wearable applications, we have investigated the practicality of implementing capacitive coupling. A capacitive coupling interface has been developed and tested with dielectric elastomer sensors underwater. Analysis of the interface's impact on sensor sensitivity, measurement electronics and overall coupling capacitor size is presented.
Diving, initially motivated for food purposes, is crucial to the oil and gas industry, search and rescue, and is even done recreationally by millions of people. There is a growing need however, to monitor the health and activity of divers. The Divers Alert Network has reported on average 90 fatalities per year since 1980. Furthermore an estimated 1000 divers require recompression treatment for dive-related injuries every year. One means of monitoring diver activity is to integrate strain sensors into a wetsuit. This would provide kinematic information on the diver potentially improving buoyancy control assessment, providing a platform for gesture communication, detecting panic attacks and monitoring diver fatigue. To explore diver kinematic monitoring we have coupled dielectric elastomer sensors to a wetsuit worn by the pilot of a human-powered wet submarine. This provided a unique platform to test the performance and accuracy of dielectric elastomer strain sensors in an underwater application. The aim of this study was to assess the ability of strain sensors to monitor the kinematics of a diver.
This study was in collaboration with the University of Auckland's human-powered submarine team, Team Taniwha. The pilot, completely encapsulated in a hull, pedals to propel the submarine forward. Therefore this study focused on leg motion as that is the primary motion of the submarine pilot. Four carbon-filled silicone dielectric elastomer sensors were fabricated and coupled to the pilot's wetsuit. The first two sensors were attached over the knee joints, with the remaining two attached between the pelvis and thigh. The goal was to accurately measure leg joint angles thereby determining the position of each leg relative to the hip. A floating data acquisition unit monitored the sensors and transmitted data packets to a nearby computer for real-time processing. A GoPro Hero 4 silver edition was used to capture the experiments and provide a means of post-validation. The ability of the sensors to measure joint angles was assessed by examining GoPro footage in the image processing software, ImageJ.
This paper applies dielectric elastomer sensor technology to monitoring the leg motion of a diver. The experimental set-up and results are presented and discussed.
Since the late 1990’s dielectric elastomers (DEs) have been investigated for their use as sensors. To date, there have been some impressive developments: finger displacement controls for video games and integration with medical rehabilitation devices to aid patient recovery. It is clear DE sensing is well established for dry applications, the next frontier, however, is to adapt this technology for the other 71% of the Earth’s surface. With proven and perhaps improved water resistance, many new applications could be developed in areas such as diver communication and control of underwater robotics; even wearable devices on land must withstand sweat, washing, and the rain. This study investigated the influence of fresh and salt water on DE sensing. In particular, sensors have been manufactured with waterproof connections and submersed in fresh and salt water baths. Temperature and resting capacitance were recorded. Issues with the basic DE sensor have been identified and compensated for with modifications to the sensor. The electrostatic field, prior and post modification, has been modeled with ANSYS Maxwell. The aim of this investigation was to identify issues, perform modifications and propose a new sensor design suited to wet and underwater applications.