Flex Sensors Research Articles

APLIKASI SENSOR KELEMBABAN DAN FLEX SENSOR BERBASIS ARDUINO UNO UNTUK SISTEM PENDETEKSI LONGSOR

Early detection of landslides is very important to minimize the number of deaths. Technological developments allow humans to predict the signs of landslides more accurately, quickly, and scientifically. In this study, sensors were tested to measure landslide disaster parameters, namely humidity sensors to measure soil moisture and flex sensors to measure soil movement. The sensor is controlled using a microcontroller Arduino Uno. A functionality test was carried out to test the ability of the sensors. The functionality test was carried out using the unit testing method. The unit testing method is carried out by comparing the functional test results of each sensor to the expected response. The moisture sensor functionality test shows that the sensor is able to respond to changes in water content in the soil with changes in voltage. The linear equation resulting from the calibration of the humidity sensor is y = -0.126x + 2.666 with R2 = 0.871. The flex sensor functionality test shows that the sensor is able to detect soil movement in the presence of changes in voltage. The linear equation resulting from the flex sensor calibration is y = -2.861x + 2507 with R2 = 0.964. This shows that the humidity sensor and flex sensor are good enough to be applied in the design of a landslide detection system.

Design and Pilot Evaluation of a Prototype Sensorized Trunk Exoskeleton.

Trunk exoskeletons are wearable devices that support wearers during physically demanding tasks by reducing biomechanical loads and increasing stability. In this paper, we present a prototype sensorized passive trunk exoskeleton, which includes five motion processing units (3-axis accelerometers and gyroscopes with onboard digital processing), four one-axis flex sensors along the exoskeletal spinal column, and two one-axis force sensors for measuring the interaction force between the wearer and exoskeleton. A pilot evaluation of the exoskeleton was conducted with two wearers, who performed multiple everyday tasks (sitting on a chair and standing up, walking in a straight line, picking up a box with a straight back, picking up a box with a bent back, bending forward while standing, bending laterally while standing) while wearing the exoskeleton. Illustrative examples of the results are presented as graphs. Finally, potential applications of the sensorized exoskeleton as the basis for a semi-active exoskeleton design or for audio/haptic feedback to guide the wearer are discussed.

WPAN and IoT Enabled Automation to Authenticate Ignition of Vehicle in Perspective of Smart Cities.

Currently, two-wheelers are the most popular mode of transportation, driven by the majority the people. Research by the World Health Organization (WHO) identifies that most two-wheeler deaths are caused due to not wearing a helmet. However, the advancement in sensors and wireless communication technology empowers one to monitor physical things such as helmets through wireless technology. Motivated by these aspects, this article proposes a wireless personal network and an Internet of Things assisted system for automating the ignition of two-wheelers with authorization and authentication through the helmet. The authentication and authorization are realized with the assistance of a helmet node and a two-wheeler node based on 2.4 GHz RF communication. The helmet node is embedded with three flex sensors utilized to experiment with different age groups and under different temperature conditions. The statistical data collected during the experiment are utilized to identify the appropriate threshold value through a t-test hypothesis for igniting the two-wheelers. The threshold value obtained after the t-test is logged in the helmet node for initiating the communication with the two-wheeler node. The pairing of the helmet node along with the RFID key is achieved through 2.4 GHZ RF communication. During real-time implementation, the helmet node updates the status to the server and LABVIEW data logger, after wearing the helmet. Along with the customization of hardware, a LABVIEW data logger is designed to visualize the data on the server side.

Low-Cost Wireless Wearable System for Posture Monitoring

Posture monitoring aiming at preventing many of the pathologies affecting the spine is becoming more and more essential in many contexts, including telemedicine. The market pushes towards the development of new technical solutions that are comfortable for the user and that are increasingly becoming lower in terms of cost. Some systems at the state of the art level are effective and sometimes quite comfortable, but they have a degree of complexity that is not compatible with some market segments. Here, we report on the development, at a prototype level, a simple, low-cost, and potentially very comfortable microcontroller-based system capable of signaling incorrect postures with great sensitivity. The prototype, which has been tested also using video analysis, has shown its capacity to be easily integrated into a garment. Experimental activity has proven the prototype’s functionality. The wearable embedded system is able to detect flections in the back region monitored by the flex sensor with an accuracy of <3°. The achievement represents a further demonstration of the potential of wearable electronics in the context of cyber-physical systems for healthcare.

Design and Performance Evaluation of a Hybrid Hand Exoskeleton for Hand Opening/Closing

Abstract Finger extensor muscle weakness and flexor hypertonia are the most commonly reported issues among patients suffering from amyotrophic lateral sclerosis (ALS). Moreover, the relative hyperflexion of the wrist and fingers has limited their ability to voluntarily open the hand and interact with the external environment. In this work, a hybrid hand exoskeleton is developed to prevent the relative hyperflexion of the fingers and wrist and facilitate the users in their functional hand opening by compensating the flexor hypertonia. This exoskeleton, combining a passive device with the soft extra muscle (SEM) glove, assists users in normal hand opening/closing required for some basic activities of daily living. The paper presents kinematic and static models of passive hand exoskeleton design. Moreover, the proposed design is tested and evaluated by comparing the volunteer hand opening with the exoskeleton assistance using the flex sensors attached on the dorsal side of the middle finger, ring finger, and thumb with both healthy subjects and patients. The results show the effectiveness of using the hybrid exoskeleton in improving anatomical hand opening/closing capabilities.

Design and Development of IoT Device that Recognizes Hand Gestures using Sensors

A hand gesture is a non-verbal means of communication involving the motion of fingers to convey information. Hand gestures are used in sign language and are a way of communication for deaf and mute people and also implemented to control devices too. The purpose of gesture recognition in devices has always been providing the gap between the physical world and the digital world. The way humans interact among themselves with the digital world could be implemented via gestures using algorithms. Gestures can be tracked using gyroscope, accelerometers, and more as well. So, in this project we aim to provide an electronic method for hand gesture recognition that is cost-effective, this system makes use of flex sensors, ESP32 board. A flex sensor works on the principle of change in the internal resistance to detect the angle made by the user’s finger at any given time. The flexes made by hand in different combinations amount to a gesture and this gesture can be converted into signals or as a text display on the screen. A smart glove is designed which is equipped with custom-made flex sensors that detect the gestures and convert them to text and an ESP32 board, the component used to supplement the gestures detected by a flex sensor. This helps in identifying machines the human sign language and perform the task or identify a word through hand gestures and respond according to it.

Design of grip strength measuring system using FSR and flex sensors using SVM algorithm

This paper proposes a design of a complete system to identify weak grip strength that is caused by multiple factors like ageing, diseases, or accidents. This paper presents a grip measurement system that comprises of force sensing resistor and flex sensor to evaluate the condition of the hand. The system is tested by gripping a pencil and a cylindrical object using the glove, to determine the condition of the hand. Force sensitive resistor (FSR) evaluates the force applied by the different parts of the palm on the object being grasped. Flex sensor evaluates the bending of the fingers and thumb. The data from the sensors is then compared with existing data to evaluate the state of the hand. The data from the sensors is stored on the personal computer (PC) through serial communication. A model is trained using the data from the sensors, which determine if the grip strength of the user is weak or strong. The model is also trained to differentiate between two modes that are pen mode and object mode. The model achieved an accuracy of 90.8 percent using support vector machine (SVM) algorithm. This glove can be deployed in medical centers to assist in grip strength measurement.

Smart Hand Glove for Hearing and Speech Impaired

Abstract: With the advancement of technology, we can implement a variety of ideas to serve mankind in numerous ways. Inspired by this, we have developed a smart hand glove system which will be able to help the people having hearing and speech disabilities. In the world of sound, for those without it, sign language is a powerful tool to make their voices heard. The American Sign Language (ASL) is the most frequently used sign language in the world, with some differences depending on the nation. We created a wearable wireless gesture decoder module in this project that can transform the basic set of ASL motions into alphabets and sentences. Our project utilizes a glove that houses a series of flex sensors on the metacarpal and interphalange joints of the fingers to detect the bending of fingers, through piezoresistive (change in electrical resistance when the semiconductor or metal is subjected to mechanical strain) effect. The glove is attached with an accelerometer as well, that helps to detect the hand movements. Simple classification algorithms from machine learning are then applied to translate the gestures into alphabets or words. Keywords: Arduino; MPU6050; Flex sensor; Machine learning; SVM classifier

Sign Language Recognition using Smart Glove

Gesture-based communication Recognition through innovation has been ignored idea even though an enormous local area can profit from it. There are more than 3% total population of the world who even can't speak or hear properly. Using hand Gesture-based communication, Every especially impaired people to communicate with each other or rest of world population. It is a way of correspondence for the rest of the world population who are neither speaking and hearing incompetency. Normal people even don't become intimate or close with sign language based communications. It's a reason become a gap between the especially impaired people & ordinary person. The previous systems of the project used to involve the concepts of image generation and emoji symbols. But the previous frameworks of a project are not affordable and not portable for the impaired person.The Main propaganda of a project has always been to interpret Indian Sign Language Standards and American Sign Language Standards and Convert gestures into voice and text, also assist the impaired person can interact with the other person from the remote location. This hand smart glove has been made with the set up with Gyroscope, Flex Sensor, ESP32 Microcontrollers/Micro bit, Accelerometer,25 LED Matrix Actuators/Output &, flex sensor, vibrator etc.

PERANCANGAN TANGAN PROSTHESIS BAWAH SIKU BERBASIS FLEXY HAND 2 DAN FLEX SENSOR

One of the best ways to rehabilitate persons with disabilities is to use prostheses. However, not all persons with disabilities, especially those with disabilities on the hands can use all types of prosthesis hands. The purpose of this research is to develop Flexy Hand 2 into a 3D Printing-based prosthesis hand that is wider in its scope of use. The method used in this research is trial and error. The scope of the user of this prosthesis hand is a person with disabilities below the elbow who still has one other hand that still has at least 3 fingers. The result of this research is a prosthetic hand that can move the entire finger and can mimic it basic hand movements such as grasping objects and picking up objects with a delay between the transmitter and receiver modules ranging from 132 milliseconds to 260 milliseconds. The entire modules works at a voltage of 5V which means the hand can be turned using a portable power supply. Keyword : Disabilities, Prosthetic Hand, Flexy Hand 2, Flex Sensor, Trial and Error.

Sign Language Recognition using Smart Glove

Gesture-based communication Recognition through innovation has been ignored idea even though an enormous local area can profit from it. There are more than 3% total population of the world who even can't speak or hear properly. Using hand Gesture-based communication, Every especially impaired people to communicate with each other or rest of world population. It is a way of correspondence for the rest of the world population who are neither speaking and hearing incompetency. Normal people even don't become intimate or close with sign language based communications. It's a reason become a gap between the especially impaired people & ordinary person. The previous systems of the project used to involve the concepts of image generation and emoji symbols. But the previous frameworks of a project are not affordable and not portable for the impaired person.The Main propaganda of a project has always been to interpret Indian Sign Language Standards and American Sign Language Standards and Convert gestures into voice and text, also assist the impaired person can interact with the other person from the remote location. This hand smart glove has been made with the set up with Gyroscope, Flex Sensor, ESP32 Microcontrollers/Micro bit, Accelerometer,25 LED Matrix Actuators/Output &, flex sensor, vibrator etc.

Operating Wheelchair Using Flex Sensor

Disabled people find their movements extremely difficult with their current gadgets. Although there are numerous devices and instruments accessible to empower their mobility, they require fine and precise control, which may be impractical in instances of higher disability. The haptic innovations are very beneficial, but demands a user friendly environment too. Strategies, designs and frameworks in this field are more in number, which depends on Joystick. But this can prove to be a big-budget. Therefore, the aim of this paper is to control a wheelchair through a utility that is budget-sensitive and practical to use. A flex sensor based wheelchair is presented in this paper, which is user friendly within a low budget. The proposed system is also accompanied by a movement monitoring system that can help the user’s kin to observe his/her movement. The aim is to provide such features which is affordable to the society and can be used with ease.

Gesture Controlled Robot using Arduino

A Gesture Controlled Car is a robot that can be controlled with a simple human touch. The user only needs to wear a touch device where the sensor is installed. The sensor will record the movement of the hand in a certain direction that will lead to the movement of the robot in the right places. The robot and the touch device are connected wirelessly with radio waves. The user can communicate with the robot in a very friendly way due to wireless communication. We can control the car using accelerometer sensors that are connected to our hand glove. Sensors are designed to replace the remote control commonly used to drive a car. It will allow the user to control the forward, backward, left and right, while using the same accelerometer sensor to control the car's steering wheel. The movement of the car is controlled by the separation method. The machine involves rotating both front and rear wheels on the left or right side to move the non-clockwise side and another pair around the clock causing the car to rotate with its axis without going forward or backward. The main advantage of this machine is that the car with this method can take sharp turns without difficulty. The design and use of a robotic control arm using a flex sensor is suggested. The robot arm is designed to consist of four moving fingers, each with three connectors, an opposing thumb, a round wrist, and an elbow. The robot arm is designed to mimic the movements of a human hand using a hand glove.

Robust Multimodal Indirect Sensing for Soft Robots Via Neural Network-Aided Filter-Based Estimation.

Sensory data are critical for soft robot perception. However, integrating sensors to soft robots remains challenging due to their inherent softness. An alternative approach is indirect sensing through an estimation scheme, which uses robot dynamics and available measurements to estimate variables that would have been measured by sensors. Nevertheless, developing an adequately effective estimation scheme for soft robots is not straightforward. First, it requires a mathematical model; modeling of soft robots is analytically demanding due to their complex dynamics. Second, it should perform multimodal sensing for both internal and external variables, with minimal sensors, and finally, it must be robust against sensor faults. In this article, we propose a recurrent neural network-based adaptive unscented Kalman filter (RNN-AUKF) architecture to estimate the proprioceptive state and exteroceptive unknown input of a pneumatic-based soft finger. To address the challenge in modeling soft robots, we adopt a data-driven approach using RNNs. Then, we interconnect the AUKF with an unknown input estimator to perform multimodal sensing using a single embedded flex sensor. We also prove mathematically that the estimation error is bounded with respect to sensor degradation (noise and drift). Experimental results show that the RNN-AUKF achieves a better overall performance in terms of accuracy and robustness against the benchmark method. The proposed scheme is also extended to a multifinger soft gripper and is robust against out-of-distribution sensor dynamics. The outcomes of this research have immense potentials in realizing a robust multimodal indirect sensing in soft robots.

Prototype Design and Development of Flex Sensor Controlled Bionic Arm for the Handicapped Person

Prototype Design and Development of Flex Sensor Controlled Bionic Arm for the Handicapped Person

Speaking System for Mute Peoples

This interacting device is a microcontroller based system which is basically outline for lessening the communication space between dumb and normal people. This system can be accordingly configured to work as a “smart device”. In this paper, Atmega 328 microcontroller, voice module, LCD display and flex sensors are utilize. The device considered is basically residing of a glove and a microcontroller based system. Data gloves are used to detect the hand motion and microcontroller based system will interpret those few manoeuvre into human place voice. The data glove is furnished with four flex sensors placed on the glove. This system is helpful for dumb people and their hand manoeuvre will be converted into speech signal because of the date glove worn on the hands.

Design and Implementation of Upper Prosthetic Controlled remotely by Flexible Sensor Glove

The structuring and the employment for a wireless prosthetic hand adjusted by a flex sensor has been suggested. The prosthetic hand has been constructed for emulating the individual arm motion utilizing a hand mitt. The hand mitt subsists of 5 flexible sensors concerning overseeing the finger motions. The animator’s design utilized to prosthetic arm has servo-motors. The fingers motions are adjusted utilizing wires which operate similarly to the tissue for an individual hand. The prosthetic hand dominates from a faraway position utilizing using remotely unit. Prosthetic hand-design equipped with many sensors; these sensors make the prosthetic hand more intelligent. The first sensor is the force sensor resistance. The second sensor is an infrared temperature sensor. This hand contains many medical applications that can be modified to become wearable for people with missing upper limbs, and the possibility of being used by doctors to perform surgeries remotely within the specified range or much further by connecting it to the internet system in addition to industrial and military applications, which is practical and low-cost. Practically tested to imitate human hand freedom movements and holding with high accuracy.

Multi-Sign Language Glove based Hand Talking System

Many people around the world suffer from losing the ability to talk and hear with different levels of disabilities, caused by either a car or a work accident or some diseases. After losing communication, these people cannot do normal functions of normal life. Along with the aforementioned disabilities, those people may also have psychological effects. This paper introduces a technique to realize multiple sign language translation using a sensors-based glove and an Android smartphone for speech impaired people to communicate normally with people. The design of the hand talking system (HTS) was implemented with a minimum possible number of sensors and a capable sewing controller (Lilypad). The proposed HTS includes flex sensors, Arduino, smartphone, and accelerometer. The HTS uses an Android application programmed to store multi-language in the SQLite database and enables the user to interact with the system. The system provides talking with a letter formed words, or using the most frequently used words in daily communication by hand gesture. The HTS has achieved high accuracy obtained for American Sign Language and Arabic Sing Language which are about 98.26% and 99.33% respectively with an average accuracy of 98.795 for both Sign Languages.

Design of Portable Exoskeleton Forearm for Rehabilitation of Monoparesis Patients Using Tendon Flexion Sensing Mechanism for Health Care Applications

Technology plays a vital role in patient rehabilitation, improving the quality of life of an individual. The increase in functional independence of disabled individuals requires adaptive and commercially available solutions. The use of sensor-based technology helps patients and therapeutic practices beyond traditional therapy. Adapting skeletal tracking technology could automate exercise tracking, records, and feedback for patient motivation and clinical treatment interventions and planning. In this paper, an exoskeleton was designed and subsequently developed for patients who are suffering from monoparesis in the upper extremities. The exoskeleton was developed according to the dimensions of a patient using a 3D scanner, and then fabricated with a 3D printer; the mechanism for the movement of the hand is a tendon flexion mechanism with servo motor actuators controlled by an ATMega2560 microcontroller. The exoskeleton was used for force augmentation of the patient’s hand by taking the input from the hand via flex sensors, and assisted the patient in closing, opening, grasping, and picking up objects, and it was also able to perform certain exercises for the rehabilitation of the patient. The exoskeleton is portable, reliable, durable, intuitive, and easy to install and use at any time.

Indonesian Sign Language Interpreter Device Based on ATMega328 Microcontroller for Bali Deaf Community Denpasar

This study aims to design and build a Sign Language Interpreter Device with Voice Output in the form of an ATMega328 Microcontroller-Based Voice Speaker Module so that in its implementation and later in designing this device the writer focuses on the translation of 16 words that have been predetermined in Indonesian Sign Language especially in Denpasar City by using a Flex Sensor and a Gyro Sensor based on the ATMega328 Microcontroller with Arduino IDE programming. This device is also equipped with a 4GB SD card memory for storing voice recordings, using an ATMega328 microcontroller, four analog Flex sensors, a Gyro sensor, a buzzer and an 8 ohm speaker, and using a 7.4 volt Li-Po battery. The application of this device is aimed for thehearing impaired people who fall into the adult category who can understand writing and understand sign language. The output of this device uses an MP3 player module that is already included in the Sign Language Interpreter Device. The flex sensor readings range from 998-1005 ADC (analog digital converter) in open conditions and the sensor ranges from 1006-10018 ADC in closed conditions. The reading for the gyro pitch (Y axis) ranges from -10º to 76º then on the reading of the gyro Roll (X axis) ranges from -100º to 90º. 
 Keywords: ATMega328 microcontroller; Buzzer; Flex Sensor; Gyro Sensor