Motion Processing Unit Research Articles

HAND GESTURE CONTROLLED WHEEL CHAIR

The project for controlling wheelchairs through gestures offers a complete solution to enhance the mobility and independence of individuals with limited motor abilities using an intuitive gesture control system. This system incorporates essential elements, such as an Arduino Nano microcontroller, MPU (Motion Processing Unit), NRF wireless communication module, 775 DC motors, and a motor driver, to allow for smooth and responsive wheelchair operation.

Dementia prediction using novel IOTM (Internet of Things in Medical) architecture framework

In the last decades the health care developments highly rise the level of ages of world population. This improvement was accompanied by increasing the diseases related with elder like Dementia, which Alzheimer’s disease represents the most common form. The present studies aim to design and implementation a medical system for improving the life of Alzheimer’s disease persons and ease the burden of their caregivers. AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patient’s future health, and recommend better treatments. AI goes beyond the foundations of deep learning to give you insight into the nuances of applying AI to medical use cases. Diagnosis is about identifying disease. By building an algorithm we can diagnosis chest X-ray and determine whether it contains disease, another algorithm that will look at brain MRIs and identify the location of tumours in those brain MRIs health of the patients lab values and their demographics and use those to predict the risk of an event. A Smart IOT Interactive Assistance is a technological device that continuously monitors the stability of an Alzheimer’s patient, indicates their position on a map, automatically reminds them to take their prescriptions, and has a call button for any emergencies they could experience during the day. The system has two components, one of which the patient wears and the other of which is an IoT platform application utilized by the caregiver. The motion processing unit sensor, GPS, heart rate sensor with microcontrollers, and LCD display were used to construct the wearable device. An Internet of Things (IoT) platform supports this device, allowing the caregiver to communicate with the patient from any location.

Poststroke Grasp Ability Assessment Using an Intelligent Data Glove Based on Action Research Arm Test: Development, Algorithms, and Experiments.

Growing impact of poststroke upper extremity (UE) functional limitations entails newer dimensions in assessment methodologies. This has compelled researchers to think way beyond traditional stroke assessment scales during the out-patient rehabilitation phase. In concurrence with this, sensor-driven quantitative evaluation of poststroke UE functional limitations has become a fertile field of research. Here, we have emphasized an instrumented wearable for systematic monitoring of stroke patients with right-hemiparesis for evaluating their grasp abilities deploying intelligent algorithms. An instrumented glove housing 6 flex sensors, 3 force sensors, and a motion processing unit was developed to administer 19 activities of Action Research Arm Test (ARAT) while experimenting on 20 voluntarily participating subjects. After necessary signal conditioning, meaningful features were extracted, and subsequently the most appropriate ones were selected using the ReliefF algorithm. An optimally tuned support vector classifier was employed to classify patients with different degrees of disability and an accuracy of 92% was achieved supported by a high area under the receiver operating characteristic score. Furthermore, selected features could provide additional information that revealed the causes of grasp limitations. This would assist physicians in planning more effective poststroke rehabilitation strategies. Results of the one-way ANOVA test conducted on actual and predicted ARAT scores of the subjects indicated remarkable prospects of the proposed glove-based method in poststroke grasp ability assessment and rehabilitation.

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.

Proposal for Gait Analysis Using Fusion of Inertial-Magnetic and Optical Sensors

A proposed measurement protocol for the lower limbs movement analysis during walking is presented, with the use of a measurement system based on inertial-magnetic motion processing units and an optical system. Initially, the state of the art in terms of methods and tools for the biomechanical capture of movements is shown, to finally explore the protocols used in the health sciences for the gait analysis. The measurement proposal made in this document uses robust features of inertial-magnetic and optical technology that can be used in medical diagnosis. The application of this proposal can generate tools that have a positive impact in the fields of health and medicine.

Peningkatan Akurasi Sensor GY-521 MPU-6050 dengan Metode Koreksi Faktor Drift

GY-521 MPU-6050 Module is a core module MPU-6050, which is a 6 axis Motion Processing Unit. This sensor can be categorized as an Inertial Measurement Unit (IMU) sensor, which utilizes measurement systems such as gyroscopes and accelerometers to estimate the relative position, velocity, and acceleration of an object. A common accuracy problem in using IMU sensors, including the GY-521 MPU-6050, is the drifting phenomenon. This phenomenon results in a deviation between the actual conditions (position, angular velocity) and the sensor readings. Drift is caused by the accumulation of errors that arise from calculating the integral of the acceleration. This study proposes a drift error correction method at the sensor output using the calibration of the calculation of the average offset error sensor and the sensor fusion method between the information obtained from the gyroscope and accelerometer in the module, the tests were carried out using the Arduino Uno microcontroller. From the test results, it is found that the combination of the initial system calibration implementation and the use of the fusion sensor concept can provide better performance with the MSE analysis results for the roll position of 0.0029o and the pitch position of 0.0047o and the drifting error rate at the yaw angle position of 0 0082o / second or down 62.72%.

Action-induced changes in the perceived temporal features of visual events

Perceived duration can be subject to deviations around the time of a voluntary action. Whether the mechanisms underlying action-induced visual duration effects are effector-specific or require a more generalized action-linked multimodal calibration with the transient visual system, however, is a question yet to be answered. Here, we investigate this using dynamic visual stimuli presented as contingent upon the execution of an arbitrarily associated voluntary manual response. Our results demonstrate that the duration of intervals with arbitrarily associated keypress–visual event pair is perceived as shorter than the duration in a pure visual condition, where the same stimuli are rather passively observed without the execution of a concurrent action. Whereas the control experiments show that motor memory and attention cannot explain the action-induced changes in perceived temporal features, action-induced changes in perceived speed are dissociated from those in perceived duration, and that the duration compression disappears using isoluminant or static stimuli, which together provide evidence that these two effects can be modulated in the motion-processing units, although via separate neural mechanisms.

A Smart Biomedical Assisted System for Alzheimer Patients

In the last decades the health care developments highly rise the level of ages of world population. This improvement was accompanied by increasing the diseases related with elder like Dementia, which Alzheimer’s disease represent the most common form. The present study aims to design and implementation a medical system for improving the life of Alzheimer’s disease persons and ease the burden of their caregivers. A Smart Biomedical Assistance is an electronic device that provide around the clock monitoring the stability state of the Alzheimer’s patient, showing their location on the map, automatically reminders for medication times, and a call button for an emergency cases that the patient may pass through during the day. The device designed with two units one worn by the patient while the other is an internet of things technology (IoT) platform application used by the caregiver. The wearable unit was implemented by using a motion processing unit sensor, global positioning sensor module (GPS), heart rate sensor with microcontrollers and LCD display. This unit is supported by an (IoT) platform for communication with the patient from anywhere by the caregiver.

SPARC: Fecobionics Simulated Defecations in Pigs

Objective. We have developed an integrated Fecobionics device to assess pressures, orientation and bending simultaneously during defecation. This study assessed the feasibility of the Fecobionics device in pigs.Methods. Ten Yorkshire pigs (male, 50–60kg) were divided into groups that was euthanized immediately after the experiment (acute group, n=5) or lived for 2 weeks before the pigs were euthanized (chronic group, n=5). Fecobionics is a bendable probe that contains pressure sensors, motion processing units (MPUs), and electronic circuits. The probe was 13cm long, 13mm OD and contained a bag for distension. The pigs were lightly restrained in a sling. The device was inserted manually through an anoscope into the rectum within half hour after the pig had a normal defecation. The bag was filled with 20–50 ml of saline to provide an urge to defecate. Behavior and signs of discomfort was evaluated during and after the defecation. Pressures, orientation and bending data were collected during defecation. Both the rectum and the anal canal were excised after euthanization for mucosal gross morphological observation and histological examination. Devices were tested after the expulsions for any damage to the electromechanical system, the core and bag.Results. The pigs paid little attention to device insertion if they were distracted by food. Often the pigs became a bit agitated after eating and defecated the device at this point. The device was defecated from few minutes up to 1h after insertion (average 12min). The pressure sensors at the two ends and inside the bag showed simultaneous pressure increase when the pigs contracted the abdominal muscle. The defecation pressure was usually in the range 80–100cmH2O if the pig was not agitated. Device bending was less than 20 degrees during defecations, indicating that the pig does not exhibit an anorectal angle like humans. Fecobionics was slowly pushed out in 10–40 seconds, often with the front hanging from the anus for some time before being dropped. The recovered devices had intact surfaces without exposed electronics. In two cases the bag had a small leak. One device stopped working after being defecated and had a broken wire, likely due to damage when it dropped to the floor. Mucosal damage, bleeding and inflammation were not found in gross morphological observation and histological examination in the acute or chronic groups.Conclusions. Fecobionics is a safe device providing novel defecatory measurements under physiological conditions.Support or Funding InformationNIH SBIR phase 1 grant R43DK112543 and NIH SPARC OT2OD025308

Smart Glove and Hand Gesture-Based Control Interface for Multi-Rotor Aerial Vehicles in a Multi-Subject Environment

This paper introduces an adaptable, human-computer interaction method to control multi-rotor aerial vehicles in unsupervised, multi-subject environments. A region-based convolutional neural network (R-CNN) first detects subjects in a frame and their faces’ regions of interest (RoIs), which are then fed to a facial recognition module to search for the main subject within the frame. The R-CNN model supplies the right-hand RoI of the main subject to a convolutional neural network (CNN) that classifies the right-hand gesture. A motion processing unit (MPU) and four flex sensors are embedded in the left hand’s smart glove to produce discrete and continuous signals. Those signals are generated based on the bending of left-hand fingers and the left hand’s roll angle and then fed to a support vector machine (SVM) to classify the left-hand gesture. Three validation layers have been implemented, including a human-based validation, classification validation, and the system validation. The comprehensive experimental results have validated the proposed method.

Modeling and Motion-control for a Light-weight Delta Robot

Delta robots are usually used for industrial manufacturing, but heavy weight and expensive price have been obstacles to rapid propagation of robots in the field. The goal of this research is to make light-weight and price-competitive delta robots. To reduce the weight, we used plastic material for the arm link, and to reduce the price, we used a step-motor as the main actuator. First we formulated the equations of inverse kinematics for the designed delta robot and then verified these equations by using multibody-dynamics simulation. An algorithm of motion control was developed and applied to the motion-processing unit using a timer-interrupt of 8 milliseconds. Finally, we tested the performance of the new delta robot by checking its control of motion along line segments.

Data Acquisition Glove for Hand Movement Impairment Rehabilitation

The present paper describes a data acquisition wearable device for hand rehabilitation. The main goal of this glove is to be used by patients with hand movement impairment. It has position sensors to measure the bending of synovial joints and sensors to measure the fingertip contact pressure. There is a coin motor and a LED placed on each finger to produce a vibratory and visual stimulus. The glove also tracks the hand rotation and translation using a MPU (Motion Processing Unit) that contains an accelerometer and a gyroscope. A graphical application for an HMI module was developed in order to create rehabilitation game like exercises where sensor data can be logged for further analysis by a therapist. The wearable device electronic hardware comprises a Glove module and an HMI module that communicate through SPI protocol (Serial Peripheral Interface). The wearable device supports USB connection to send data to a computer or to be used as a peripheral device in virtual or augmented reality applications.

Bezzałogowa zdalnie sterowana jednostka latająca

Quadrocopter as an example of a dron that is used both in a public and industrial sectors. First of all the authors designed and manufactured frame of the device. Then they chosen elements which allow the quadrocopter to flight. There is the central unit in the form of a microcontroller ATmega 644PA on board. In next part the authors explained the programming process of the elements of a quadrocopter control program. The control system for stabilization of the machine requires the information about the location of quadrocopter in space. This is done by motion processing unit which contains an accelerometer and gyroscope. The quadrocopter to fly needs commands from the operator. It has been decided to implement controlling via Bluetooth module and hand-written application on

A new motion illusion based on competition between two kinds of motion processing units: The Accordion Grating

Parametric psychophysical investigations are reported for two related illusory effects that occur when viewing an elementary square-wave grating while making "back and forth" head movements along the projection line. Observers report a non-rigid distortion of the pattern, including: (i) an expansion in a direction perpendicular to the stripes, and (ii) a perceived curvature of the stripes. We investigated these two phenomena independently. The first depends on the classical physiological aperture problem that confronts early cells in the vision system. Interactions between ambiguous and unambiguous motion signals, generated at line interiors and line ends, respectively, can explain why the perceived expansion occurs only in directions perpendicular to the stripes. A simple model is presented and successfully tested by a nulling psychophysical experiment with four subjects. The experiment varies key stimulus attributes that generate ambiguous and unambiguous motion signals. Regarding the illusory curvature, a differential geometry model of the optics of our display, which identifies a non-classical three-dimensional (3D) aperture problem, is proposed(Yazdanbakhsh & Gori, 2011). We tested that model by implementing its closed form prediction of distortion to design displays for a second psychophysical experiment that also uses a nulling technique. Results from four subjects allow the quantification of the degree of perceived curvature as a function of speed, distance and stimulus type (blurred vs. unblurred grating) and are compatible with the predictions of the model.

Different motion sensitive units are involved in recovering the direction of moving lines

We studied direction discrimination for lines moving obliquely relative to their orientation. Manipulating contrast, length and duration of motion, we found systematic errors in direction discrimination at low contrast, long length and/or short durations. These errors can be accounted for by a competition between ambiguous velocity signals originating from contour motion processing units and signals from line terminator processing units. The dynamic of this competition can be described by a simple model involving two different classes of processing units with different contrast thresholds, different integration time constants and different levels of response saturation.