Gyroscope Research Articles

Alert System for Fall Detection

Abstract: Healthcare is one of the most important industries, yet new ideas must travel a long way before being fully adopted due to its complexity, scope of duty, and stringent laws. The Internet of Things (IoT) may be the key to resolving healthcare challenges. The Internet of Things (IoT) has a lot of potential in healthcare, but it's still in its early stages. With the advancement of medical IoT, new possibilities for telemedicine, remote monitoring of a patient's status, and much more will emerge. Falling is a significant health danger for the elderly. If the problem is not detected in a timely manner, it can result in the death or impairment of the elderly, lowering their quality of life. Falls are a major public health concern for the elderly around the world. When it comes to old age, we must keep an eye on our loved ones to ensure their health and safety. It is therefore critical to determine if an elderly person has fallen so that help can be provided promptly. Proposing a person fall detection system based on a wearable device for detecting the falls of people in every situation, which takes advantage of lowpower wireless sensor networks, smart devices, and analyses human body motions. The system detects movement using an accelerometer and a gyro sensor. The sensor is wired to a microprocessor, which transmits the acceleration data continuously. Fall detection and sudden movement changes in the person would be monitored by the system. The sensors are getting values from a quick movement shift with shock in the system. When a person falls and becomes unconscious, the system determines whether the person has indeed fallen. If the person has truly fallen, the system will send an alert to the caregivers and sound an alarm to alert anyone nearby. When the system detects that a person has fallen, it immediately sends an alert to the individual's care takers. It is an IoT-based fall detection system that assists people by telling their caregivers about their fall so that quick attention may be drawn to the situation and essential actions can be taken to save the person who has fallen. Keywords: Threshold Based Fall Detection, Arduino, Bi-Axial, Accelerometer, Gyroscope,

QUANTITATIVE ANALYSIS OF ESSENTIAL TREMOR DURING CLINICAL SPIRAL DRAWING TASK USING GYRO SENSORS

The spiral drawing task is a representative clinical test used to assess essential tremor. Many clinicians have used spirography to assess through visual rating of the drawings. We quantitatively investigated the clinical characteristics of action tremors during spiral drawing tasks using 3-axis gyro sensors. Eighteen essential tremor patients with sensors attached to their forefinger, dorsum of the hand, and forearm participated in a spiral drawing test. As quantitative variables, the average speed, maximum frequency and maximum power were derived from the gyro sensor signals. The average speed and maximum power were also logarithmically transformed. Two-way repeated measures analysis of variance (ANOVA) with tremor direction and joint (attachment location) as independent factors was performed to evaluate the main and interactive effects of direction and joint. Also, Spearman’s correlation analysis was performed to evaluate the relationship between the quantitative variables and visual rating scores. The average speed showed a significant main effect of direction ([Formula: see text]). Logarithmic variables showed interactive effects ([Formula: see text]) as well as main effects ([Formula: see text]). The interactive effects were attributed to no significant difference among the joints particularly in the roll direction ([Formula: see text]). The logarithmic variables of roll direction were significantly greater than that of the other directions ([Formula: see text]). Also, the quantitative variables were moderately correlated with visual rating scores ([Formula: see text], [Formula: see text]). These results indicate that kinetic tremor during spiral drawing mainly appears in the roll direction and may contribute to the determination of sensor location and direction for continuous monitoring of patients with essential tremor.

Design of hoeckens linkage based walking robot with MPU6050 IMU as navigation sensor

This article introduces a 4-legged walking robot using Hoeckens Linkage. In some applications, a legged robot is preferred if compared with a wheeled robot because it has a more considerable degree of freedom and can move on uneven surfaces. Hoeckens Linkage is one of the linkages that can convert rotational motion to approximate straight-line motion, which allows the robot to move faster than other linkages. This robot is designed using SolidWorks to simulate the Hoeckens linkage path, and its structure is built using 3D printed parts. Arduino Mega was used as a microcontroller to process the feedback signals so that the robot able to move in the desired pattern. The hall effect encoders were used so that DC motors always rotate with the desired RPM regardless of walking surfaces and power supplied to them. MPU 6250 gyro sensor also be used in this walking robot as a navigation sensor. Gyro sensor allows the robot to travel in a straight line or rotate a certain degree by computing yaw value from its raw data and DC motors’ control speed using a P controller. The speed average of the fabricated robot is 3.00 m/min.

Design and implementation of monitoring system for paralysis patient using IoT

Internet of things represents a catch line of smart applications. At the same time it plays a leading role in the health care systems, as it provides the connectivity of the distant patients, who are not able to express their concerns. In this modern era there are a lot of technologies that are being used in different healthcare fields for paralyzed people. This paper proposed a model for paralyzed patient by considering Arduino with the integration of gyro sensors for the patient hand and finger movement. Patient can easily be connected with this device by sending his message to caretaker only by moving their hands into respective directions, or they can send their message by moving their fingers and feet. Through this device paralyzed patient will be able to convey their messages to caretakers, so they can assist the patient. This system will enhance the medical care to those patients who are even not able to convey their message.

Wireless data transfer with the use of internet of things (IoT) technologies in smart textiles

IoT devices, which have become an indispensable part of our lives, attract more attention day by day, especially in smart cities. Use of IoT devices on textiles reveals smart textile equipment. In this work, the elbow joint angle of the person can be measured with 2 accelerometer and gyro sensor integrated on the textile. It is one of the first studies to measure the elbow joint angle by placing a sensor on textile and wirelessly transfer it to the computer in real-time in the literature. In our present work, angle measurement process has been carried out on a platform where calculations are made on the Arduino microcontroller using IoT devices. By performing experiments with the smart textile prototype created, its performance has been evaluated. The high performance values show that the elbow joint angles of the individuals can be measured reliably with the designed prototype.

A new approach for physical human activity recognition based on co-occurrence matrices.

In recent years, it has been observed that many researchers have been working on different areas of detection, recognition and monitoring of human activities. The automatic determination of human physical activities is often referred to as human activity recognition (HAR). One of the most important technology that detects and tracks the activity of the human body is sensor-based HAR technology. In recent days, sensor-based HAR attracts attention in the field of computers due to its wide use in daily life and is a rapidly growing field of research. Activity recognition (AR) application is carried out by evaluating the signals obtained from various sensors placed in the human body. In this study, a new approach is proposed to extract features from sensor signals using HAR. The proposed approach is inspired by the Gray Level Co-Occurrence Matrix (GLCM) method, which is widely used in image processing, but it is applied to one-dimensional signals, unlike GLCM. Two datasets were used to test the proposed approach. The datasets were created from the signals obtained from the accelerometer, gyro and magnetometer sensors. Heralick features were obtained from co-occurrence matrix created after 1D-GLCM (One (1) Dimensional-Gray Level Co-Occurrence Matrix) was applied to the signals. HAR operation has been carried out for different scenarios using these features. Success rates of 96.66 and 93.88% were obtained for two datasets, respectively. It has been observed that the new approach proposed within the scope of the study provides high success rates for HAR applications. It is thought that the proposed approach can be used in the classification of different signals.

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

센서 융합 기반의 배추 수확기 예취부 3축 자세 제어

In Korea, Chinese cabbage harvesting is insufficiently mechanized and automated, and this task is typically carried out using manual labor. Thus, research on Chinese cabbage harvesters is required. However, the terrain in cabbage fields is generally rough and comprises many obstacles. Consequently, problems such as overcutting, missed cutting, and side cutting occur while cutting cabbages using a cabbage harvester. Therefore, it is necessary to study the cutting mechanism of the harvester to perform accurate cutting, considering the terrain in the fields. To this end, a three-axis attitude control mechanism was designed in this study; this mechanism controls the cutting device of the Korean cabbage harvester with three cylinders. In addition, an accelerometer, a gyro sensor, and a rotary encoder were designed for sensor fused. The cylinders were controlled such that the measured roll (Φ) and pitch (θ) were level with the ground. In addition, the angle of the guide in the cutting device (θ<SUB>e</SUB>), driven by grounding to the ground, was calibrated using the height data. The cylinder in the sliding (x) axis was controlled to maintain the target height. Further, a proportional-integral-derivative controller was integrated to reduce overshoot and improve stability. To assess the performance of the algorithm, a 2:1 scaled-down model of the cutting device of the Korean cabbage harvester was produced, and the attitude control mechanism was installed on its driving platform and tested. Attitude measurement was performed using a motion capture device (OptiTrack). For quantitative evaluation, data with and without the attitude control system were compared by estimating their root mean square error (RMSE). The RMSE values for the level and height were 0.89° and 2.23 cm, respectively, for attitude control with the posture control system; however, those for attitude control without the posture control system were 2.15° and 4.05 cm, respectively. In addition, improvements of 58% in the level control and 45% in the height control were observed. In further investigations, better results can be obtained using the harvester if the changes in the angle and height are higher than those obtained in this experimental environment.

Design and Error Verification of Intravenous Injection Detection System that Combines Load Cell and Gyro Sensor

Design and Error Verification of Intravenous Injection Detection System that Combines Load Cell and Gyro Sensor

RETRACTED ARTICLE: Smart wearable medical devices for Isometric Contraction of muscles and joint tracking with gyro sensors for elderly people

People with a healthy lifestyle modulate cycles of stimulation through posture and social factors. In general, muscle activation is generally controlled by exoskeleton patterns, mainly personal muscle control during voluntary movement. Therefore, a survey suggested that Persons with nervous system disorders and older people cannot modulate their muscle activity rhythm and have issues with movement control. Hence, this study concentrates on Linear Quadratic Estimation Hybridised Computer Algorithm (LQE-HC) to detect the muscles’ behaviour method using accelerometers to find joints’ angular speed. Remote monitoring can give valuable data on the regular exercise level and functional potential of individuals. Furthermore, a low drift in the observed speed leads to a longer integration error. Supplementary data from gyroscopes are normally fused with the Linear Quadratic Estimation (LQE). A computer algorithm structurally measures instructions to a wearable device to conduct an optimal muscle stimulation sequence inducted for goal muscle powers. This article introduces a basic principle, conceptual description, and method for the human muscular force regulation and its adaptation to a motor system with upper extremity exoskeleton-type wearable devices.

Wearable Medical Gyro Sensors Based on Joint Tracking for Elderly

This article concentrates on Linear Quadratic Estimation Hybridised Computer Algorithm (LQE-HC) which has been proposed to detect the behavior method of muscles with the implementation of accelerometers to find the angular speed of joints. Remote monitoring can give valuable data on regular exercise level and functional potential of individuals. Furthermore, a low drift in the observed speed leads to a longer integration error. Supplementary data from gyroscopes are normally fused with the Linear Quadratic Estimation (LQE). A computer algorithm structurally measures instructions to a wearable device so that an optimal muscle stimulation sequence is inducted for goal muscle powers.

Measurement of Mud Motor Back-Drive Dynamics, Associated Risks, and Benefits of Real-Time Detection and Mitigation Measures

SummaryNorth American shale drilling is a fast-paced environment where downhole drilling equipment is pushed to the limits for the maximum rate of penetration (ROP). Downhole mud motor power sections have rapidly advanced to deliver more horsepower and torque, resulting in different downhole dynamics that have not been identified in the past.High-frequency (HF) compact drilling dynamics recorders embedded in the drill bit, mud motor bit box, and motor top subassembly (top-sub) provide unique measurements to fully understand the reaction of the steerable-motor power section under load relative to the type of rock being drilled. Three-axis shock, gyro, and temperature sensors placed above and below the power section measure the dynamic response of power transfer to the bit and associated losses caused by back-drive dynamics. Detection of back-drive from surface measurements is not possible, and many measurement-while-drilling (MWD) systems do not have the measurement capability to identify the problem. Motor back-drive dynamics severity is dependent on many factors, including formation type, bit type, power section, weight on bit, and drillpipe size. The torsional energy stored and released in the drillstring can be high because of the interaction between surface rotation speed/torque output and mud motor downhole rotation speed/torque. Torsional drillstring energy wind-up and release results in variable power output at the bit, inconsistent rate of penetration, rapid fatigue on downhole equipment, and motor or drillstring backoffs and twistoffs.A new mechanism of motor back-drive dynamics caused by the use of an MWD pulser above a steerable motor has been discovered. HF continuous gyro sensors and pressure sensors were deployed to capture the mechanism in which a positive mud pulser reduces as much as one-third of the mud flow in the motor and bit rotation speed, creating a propensity for a bit to come to a complete stop in certain conditions and for the motor to rotate the drillstring backward. We have observed the backward rotation of a polycrystalline diamond compact (PDC) drill bit during severe stick-slip and back-drive events (−50 rev/min above the motor), confirming that the bit rotated backward for 9 milliseconds (ms) every 133.3 ms (at 7.5 Hz), using a 1,000-Hz continuous sampling/recording in-bit gyro. In one field test, multiple drillstring dynamics recorders were used to measure the motor back-drive severity along the drillstring. It was discovered that the back-drive dynamics are worse at the drillstring, approximately 1,110 ft behind the bit, than these measured at the motor top-sub position. These dynamics caused drillstring backoffs and twistoffs in a particular field. A motor back-drive mitigation tool was used in the field to compare the runs with and without the mitigation tool while keeping the surface drilling parameters nearly the same. The downhole drilling dynamics sensors were used to confirm that the mitigation tool significantly reduced stick-slip and eliminated the motor back-drive dynamics in the same depth interval.Detailed analysis of the HF embedded downhole sensor data provides an in-depth understanding of mud motor back-drive dynamics. The cause, severity, reduction in drilling performance and risk of incident can be identified, allowing performance and cost gains to be realized. This paper will detail the advantages to understanding and reducing motor back-drive dynamics, a topic that has not commonly been discussed in the past.

Global exponential attitude tracking for spacecraft with gyro bias estimation

Relying on contraction analysis, this paper addresses the global attitude tracking problem of a spacecraft when angular velocity measurements are corrupted by bias. A nonlinear observer with exponential convergence is designed firstly to estimate the bias in gyro sensors. Then an exponentially convergent attitude tracking controller with gyro bias correction is devised. Next, to remove the topological constraints of unit quaternions for global stability, a switching variable with hysteresis is incorporated in the control loop, enhancing the robustness in the presence of measurement noise and energy efficiency by preventing the unwinding phenomenon. Numeric simulations are shown to illustrate the performance and compare with other similar controllers in terms of tracking error, estimation error and energy efficiency, as well as the robustness to noisy measurements and time-varying bias in gyro sensors.

Penmanship and signal acknowledgment utilizing inertial pen

This paper exhibits an inertial-sensor based advanced pen, connected with Dynamic Time Traveling calculation for penmanship and signal acknowledgment. With favoured dealt with speed, client holds inertial pen to compose numeral or lowercase literatures and make indicator signals. The signs from accelerometer and gyro sensor are coordinated and gathered into a quaternion-based reciprocal channel to lessen the vital blunders from the gyro sensor which causes the inherent commotions and sign float are here and there diminishes the exactness of the direction estimation. This uses DTW based acknowledgment calculation with which it comprises of different structures like preparing, recognizable proof and afterward the recognition part. To get a prevalent class detachment for improved acknowledgment we have created to negligible between class to maximal class-based format determination technique. In the Trial results, the adequacy of the DTW-based calculation for web-based penmanship and motion utilizing the inertial pen is effectively approved.

Pipeline Mapping using a Towed Unit Equipped with a Wheel Encoder and a Gyro Sensor

Pipeline Mapping using a Towed Unit Equipped with a Wheel Encoder and a Gyro Sensor

INVESTIGATION OF USER INTERFACE OF GYRO-SENSOR-BASED HAND GESTURAL DRONE CONTROLLER

Joystick controllers are used mainly for modern civil drones. However, joystick controllers are non-intuitive and require two hands to be used simultaneously. Therefore, although single-handed drone controllers using a joystick and hand gestures have been introduced, they have only replaced the right stick of the joystick controller with gyro sensors. While this approach retains interface continuity with conventional joystick controllers, it is not user-centric. Therefore we propose a gestural drone controller based on hand gestures, and compare it experimentally with conventional controllers, including an investigation of the effective differences depending on the user’s joystick experience. We separateparticipants into expert and novice joystick groups to investigate the joystick controller experience effects (e.g., radio-controlled cars, game consoles) for each controller type. The conventional joystick controller is found to be superior to the conventional gestural controller for five out of nine criteria, and superior to the proposed gestural controller for three out of nine criteria. The proposed gestural controller is more natural than the conventional gestural controller. There tends to be an interaction effect of the joystick experience and controller types, considering the naturalness of the controller.

On-board Relative Attitude Determination and Propagation Using Earth Sensor

In this paper, we propose methods to determine and propagate relative attitude using an earth sensor. Three-axis attitude determination using the Earth sensor is advantageous in terms of space consumption, but it is a fault that we cannot always use it. By detecting and propagating relative attitude information, we attempt to fill that time gaps. The difficulty is that the spacecraft cannot ignore its own translational movement when it looks at the earth, unlike when it looks at the stars. In this research, the attitude and position estimation method used in computer vision is applied instead of the traditional attitude determination method for spacecrafts used in STT and so on. The algorithms use the movement of a point common to two images taken with a time interval, and the translational movement information of the spacecraft obtained from orbit information. The obtained relative attitude is propagated using a Kalman filter to estimate the absolute attitude. The proposed algorithms are evaluated by numerical simulations. The results are as accurate as small MEMS gyro sensors, suggesting the possibility of being replaceable in the future.

Indoor Floor Localization Based on Multi-Intelligent Sensors

With the continuous expansion of the market of indoor localization, the requirements of indoor localization technology are becoming higher and higher. Existing indoor floor localization (IFL) systems based on Wi-Fi signal and barometer data are susceptible to external environment changes, resulting in large errors. A method for indoor floor localization using multiple intelligent sensors (MIS-IFL) is proposed to decrease the localization errors, which consists of a fingerprint database construction phase and a floor localization phase. In the fingerprint database construction phase, data acquisition is performed using magnetometer sensor, accelerator sensor and gyro sensor in the smartphone. In the floor localization phase, an active pattern recognition is performed through the collaborative work of multiple intelligent sensors and machine learning classifiers. Then floor localization is performed using magnetic data mapping, Euclidean closest approximation and majority principle. Finally, the inter-floor detection link based on machine learning is added to improve the overall localization accuracy of MIS-IFL. The experimental results show that the performance of the proposed method is superior to the existing IFL.

Design of Wheel Chair Up Stairs at Station for Disability People

Intelligent wheelchairs are motorized resting media designed to help users with physical limitations, where an artificial control system is added or used to replace user controls. The aim is to reduce or eliminate the user's duty to drive a motorized wheelchair. At the station there are still many places that are still not accessible by persons with disabilities. As the difference between platform and train height, usually there are stairs that support to enter the train. Therefore the writer makes an innovation so that it can make it easier for people with disabilities to move up stairs in a wheelchair. The design of the wheelchair design uses a crawler type with the help of universal plates from Tamiya, the gearbox uses Twin Motor with a rotation ratio of 204: 1. Servo motor mounted on the seat which is supported by a gyro sensor as a counterweight to the chair when the position of the chair up or down. In the DC motor and servo PID method is added so that the motion changes can be smooth. PID is installed when testing the equilibrium results obtained a little stable oscillation at Kp = 0.27, Ki = 0.0004, and Kd = 0.0001, while when testing the speed obtained the most stable conditions at Kp = 2, Ki = 1, Kd = 0.25.

Gyro-Sensor-Based Vibration Control for Dynamic Humanoid-Robot Walking on Inclined Surfaces.

An efficient motor-control system for stable walking of the lightweight humanoid robot KONDO KHR-3HV on inclined surfaces is investigated. The motor-control system is based on the angular velocity of the pitch motion of the robot, which is detected by a gyro sensor attached to the robot torso and referred to as the angular-pitch velocity. The robot gait is analyzed for different downslopes with and without the motor-feedback control. A novel method of frequency-domain analysis of the angular-pitch velocity is proposed for explaining the reasons behind the instabilities of dynamic humanoid-robot walking on inclined surfaces. The results show, that a nonlinear nature of the motor torque, due to a force induced by the slope, gives rise to harmonics of the fundamental walking frequency of 1.73 Hz. These harmonics are the origin of the unstable robot walking. Additionally, the feedback-gain parameters KA and KH affect the amplitudes of the harmonics, which give rise to vibrations at a higher surface inclination. Increased surface friction allows a reduction of the feedback gain, which reduces this specific contribution to the harmonics and thus stabilizes the robot. To improve the walking stability on inclined surfaces, it is found that the damped natural frequency of the motor-control system must be kept lower than the fundamental walking frequency.