Application Of Flexible All Graphite Paper Based Field Effect Transistor For Motion Detection Using Strain Sensing

There is an explosive growth in wearable computing devices over the past couple of years mostly due to technological advances in smart devices. Although most of these are self-care monitoring devices the need for assisted living where a patient can be monitored continuously using these devices are emerging fast. In a typical monitoring system, various vital biological signals, fall risks and changes in predetermined health conditions are collected via sensors and shared with health care professionals for intervention if necessary. Most popular applications of self-care monitoring include daily activity monitoring, emergency and fall detection and rehabilitation. Despite these useful applications, the paradigms such as autonomy, context awareness and spontaneous interactions are not well integrated into these existing systems yet.

Essential tremors, the most common form of tremors, are prevalent at some scale in approximately 98% of the elderly population. This type of tremor becomes more severe with age, rendering simple daily tasks such as cooking and writing very difficult, due to the involuntary movement. With such a large percentage of senior citizens affected, much of the population would benefit from a solution to this issue. Therefore, this study demonstrates an experimental design that has been created to reduce oscillations caused by the tremors, thus increasing hand dexterity in tremor sufferers. To do this, a combination of gyroscopes and weight were made into a glove that patients could wear to counteract movement from the tremor, allowing the patient to

It can be used in conjunction with spacewalks or independently, such as the Canada arm on the ISS. The design is a glove that an astronaut within the ISS would wear, and sensors would detect the amount of flex and power the astronaut is using while also offering resistance according to the task. It would essentially work as a normal hand would, without the astronaut having to perform tasks in cumbersome gloves while conducting an EVA- the astronaut within the station would manipulate the autonomous hand. NASA has begun working on a similar innovation, the Human Grasp Assistance Device, which provides grasping support for human fingers using pressure sensors. The fingertips of the glove detect when the user is grasping a tool and pull the fingers into a gripping position- holding them there until the sensor is released, lowering the fatigue levels of the astronaut

Human motion capture is being used for more and more things. It is being used in the clinical setting to define problems in gait or other athletic movements. Motion capture is also being used in the field of entertainment to animate movies and video games. We can track human movement through a variety of mechanisms. The most common is to use cameras and reflective markers to track how the person is completing a movement. There are downfalls within each of the ways to track movement. For example, when using markers and cameras, each marker has to be seen at all times by at least two cameras. Also, the markers need to be placed directly on the skin otherwise they can move causing unnecessary data. And the placement of markers can take an unnecessarily extended amount of time to position. The goal of this paper is to address different ways and downfalls of each way to capture human motion. This paper will also address new possible ways to track human movement in a simple and time-efficient manner.

In the research paper Wearables, Social Networking and Veracity: The Building Blocks of a Verified Exercise Application by Chiung Ching Ho and Mehdi Sharifi, the numbers of work based on weight lifting exercises are low as compared to work related to motion recognition exercise while according to them these two exercises are equally important.

Our design does not use a lot of human body to control the system. The users will their left arm to wear the smart watch and lift their arm to view all the different types of controllers. As you can see in the figure below, the users can use any of their fingers to go through the controllers in the smart watch system to control the control the drone. We suggest that the users use their index finger or middle finger. With their index finger, the users can set the distance between them and the drone, the angle of the drone, and the positive

Various researches results several observational methods, which has focus on the different of body segments. Rapid Upper Limb Assessment

dorsaVi presents solid real-time motion analysis device technologies, and for the first time, the device is able to accurately capture assessments up to 24 hours. This is more effective than going to an off-site facility to do fitness and biometric exams that could longer than that to produce results. dorsaVi focuses on three aspects:

Currently the design consists of different components from multiplying sources. The fingers are connected with rubber rings, ropes. Gripper motors are attached to the finger to decrease the friction. But these connections may become loose or unstable after the frequent hand movement. The rope is left outside of the glove at present. If there is a twist between different ropes, errors will occur during the control of the finger movement. We found the tubing near the two ends of the air muscle have more possibility to explode. The reason is both tubing and Sleeving have an irregular shape near the clamps and more friction happens in these areas. Also the contraction percentages of the muscles are only 75%, but the real muscles have contractions

To justify the idea the proposed, a series of experiments are undertaken. This consists of implementing the system into a real smart home with a single power analyser at the main electrical panel. The assistive system was tested rigorously against real life scenarios, related to morning ADL to test the accuracy and how competent the system is to assist patients in a real life context, algorithm for assistance is implemented within the system for the activity recognition every time an electrical appliance is used. The authors determined potential errors or abnormal situations to test out any inconsistent behaviour which should cause a prompt to be sent to the patient to provide the appropriate

Abstract: Electromyography is a method to evaluate levels of muscular activity. When a muscle fiber contracts, an action potential is generated and this circulates along the muscular fibers. In electromyography, electrodes are connected to the skin and the electrical activity of muscles is measured and graph is plotted. The surface electromyography signals selected during the muscular activity are interfaced with a system. The EMG signals from individual suffering from Neuropathy and healthy individual, so obtained, are processed and analyzed using signal processing techniques. This project includes the investigation and interpretation of EMG signals of healthy and Neuropathic individuals using MATLAB. The prospective utilization of this study is in developing the prosthetic device for the people with Neuropathic disability.

Initially survey of many patients with different gait abnormalities was done by which we found that there were different types of gaits. The patients were affected in different parts of the body and were a part of gait analysis known by different names. The present and the existing devices were also studied and was found that these devices provided analog output. Analog signals had distortion which creates a loss of signals and it is able to recover the attenuated signals. These were the disadvantages which were taken as the objectives of the project. Hence, we decided to go for a digital output to provide accurately and quantify the output. The existing way of treating the patients was very costly and the results need to the processed by using video camera etc. The cost of the device was high which was not affordable by all people. Hence, there was a need to develop the portable device which helps in measuring gait parameters by digital sensors and provide assistance in taking the value of these parameters

Using the tools on logger pro, the force sensors were calibrated. A 20-cm string was attached to the hooks connected to the end of each sensor. After being attached, logger pro started collecting the data and the two sensors were pulled apart by one person. Logger Pro automatically provided a graph with the data provided with the sensors. This part was repeated with an elastic band that was attached to the two ends of the sensors. The graphs provided were saved and was used to analyze the force pairs.

Graphene is a hexagonal two-dimensional (2D) monolayer of honeycomb lattice packed carbon structure that was discovered and successfully isolated from bulk graphite just a few years ago [1]. It is a promising candidate in a number of mechanical, thermal and electrical applications [2-6], owing to its outstanding physical properties [2]. In addition to enormous nano-technological applications, graphene also attracts prodigious attention as strengthening element in composites [7-10]. Characterization of the mechanical properties of graphene is essential both from a technological perspective for its reliable applications and from a fundamental interest to understanding its deformation physics [11-13]. In material science, fracture toughness is a property that describes the ability of a material containing a crack to resist fracture, and is one of the most important mechanical properties of any material [14-15]. The useful strength of large area graphene with engineering relevance is usually determined by its fracture toughness, rather than the intrinsic strength

The mechanical properties of graphene sheet can be tailored with the help of topological defects. In this research article, the effects of Stone-Thrower-Wales (STW) defects on the mechanical properties of graphene sheet was investigated with the help of molecular dynamics (MD) based simulations. Authors has made an attempt to analyse the stress field developed in and around the vicinity of defect due to bond reorientation and further systematic evaluation has been carried out to study the effect of these stress fields against the applied axial compressive load. The results obtained with the pristine graphene were made to compare with the available open literature and the results were reported to be in good agreement with theoretical and experimental data. It was predicted that graphene with STW defect cannot able to bear compressive strength in zigzag direction, whereas on the other hand it was predicted that graphene sheet containing STW defect can bear higher compressive load in armchair direction, which shows an anisotropic response of STW defects in graphene. From the obtained results it can be observed that orientation of STW defects and the loading direction plays an important role to alter the strength of