Top PDF Design Of Motion Detection Using Tri-Axial Accelerometer For The Elderly

Design Of Motion Detection Using Tri-Axial Accelerometer For The Elderly

Design Of Motion Detection Using Tri-Axial Accelerometer For The Elderly

In addition, the benefit of fall detector is that it can minimize the time the elderly remain lying on the ground after falling known as “long lie”. The important factor that define the severity of the fall is within this period of time. Most of the ageing people are unable to stand up again if there is not support has given and the continuous long lie can cause dehydration, hypothermia, pressure sores and bronchopneumonia [3]. This case is even worse if the elderly lives with their own or loss of consciousness after experience a fall. Fall detector is still not a popular devices used and do not see any significant impact on the old people yet. Most of the latent users do not be aware of this system but once the concept is delivered, they realize that it was such a helpful devices to alter their safety and security in house [3].
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Fall Detection System Using Tri-Accelerometer for Wireless Body Area Network

Fall Detection System Using Tri-Accelerometer for Wireless Body Area Network

Abstract: In this paper, we observe the physical condition of elderly people or patients in personal environments such as home, office, and restroom. The elderly peoples mostly have limited physical abilities and are affected with serious physical damages even with small injuries like fall. The falls are not predictable also not avoidable. In case of a fall, its early detection with notification to emergency services is essential for quick recovery. The existing fall detection devices are more bulky and uncomfortable to wear. In this paper, a new fall detection system is used which includes tri-axial accelerometer sensors to classify the behavior and posture of the detection subject. Body motion can be classified into different patterns, i.e. vertical position, lying position, sitting position, horizontal position and fall. If a fall is suspected, an automatic message can be sent (GSM) with fall location (GPS). The major advantage of the proposed system is the use of mobile phone which is readily available to most people[1][2].
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Evaluation of Three-Axial Wireless-based Accelerometer for Fall Detection Analysis

Evaluation of Three-Axial Wireless-based Accelerometer for Fall Detection Analysis

The measurement setup in this project is based on the method that had been introduced by Chia-Chi Wang et al. [12] which set the position of the sensor at the waist. The accelerometer is placed at the front waist which is near the center of body mass as in Figure 3. The site of signal detection prefers waist because this placement has several advantages compared with wrist, knee, head and neck which are near the center of body mass and capable to provide more reliable information on body movements since it is less affected by sudden limb motion artifacts. Furthermore, the use of a belt at a waist is generally perceived by elderly persons as non-invasive.
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ANDROID APPLICATION FOR FALL DETECTION USING TRIAXIAL ACCELEROMETER

ANDROID APPLICATION FOR FALL DETECTION USING TRIAXIAL ACCELEROMETER

The purpose of this project is to design and produce a system to monitor the fall of patients and track the position of fall using global positioning system (GPS) and global system for mobile communication (GSM) Technology effectively. This project is also used for measuring and calibration of the joint movement, this paper describes system for monitoring and fall detection of patients using tri axial accelerometer along with ZigBee transceiver to detect fall of patient’s .The system is composed of data acquisition, fall detection and data base for analysis
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Infant Monitoring and Fall Avoidance System using Tri Axial Accelerometer and ARM7 Microcontroller

Infant Monitoring and Fall Avoidance System using Tri Axial Accelerometer and ARM7 Microcontroller

In the robotics field, human gestures have been recognized, by attempting several researches, using vision based systems [10] [11], sensors capturing motion [12] [13], or using active tracking mechanism based finger gesture recognition systems [14]. The activity of the infant is a major concern in this research, which further decides the way of monitoring and controlling. The gestures of infant can be recognized by implementing the following two systems: sensor-based and vision based, [15].The sensor-based solutions use accelerometers or gyros for detecting the gestures. When gestures are done with the hands, a special glove or special device kept in hand is used. When gestures are done with the body, sensors are mounted on the part of the body used for communication. This paper presents a body gesture recognition system built around an accelerometer sensor. The whole system consists of an accelerometer which the infant wears on himself, local units to collect data that are placed in infant’s vicinity and systems for collecting, processing and displaying the calibrated data. The system is divided into two units. One is the monitor and fall control unit and the other unit is data acquisition unit, which consists of the infant wearing accelerometer (ADXL335), which is small and lightweight and transmits command packets to ARM7microcontroller. The monitor and fall control unit consists of a processing unit (ARM7 microcontroller), 16×2 LCD, Switch keypad and Buzzer. LCD shows the calibrated output values. ARM7 microcontroller has inbuilt ADC, which converts the obtained analogue signal into the digital output and Buzzer provides a sound signal showing the fall detection resulting into appropriate actions to take place. A wired connection is provided between both the units, which helps in communicating between them.
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Motion Detection Using Passive Infrared Sensor

Motion Detection Using Passive Infrared Sensor

For nowadays, we will switch OFF the light when we are going out from the office or sleep in the bedroom. However, some people might wake up during at night. When they wake up, their mental might not so clear and it is hard for them to find the switch to switch ON the light. Therefore, if they have a motion detection system to switch ON the light automatically, it is easier for them to avoid cannot find a switch and occur accident.

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Motion Detection using Frame Subtraction and Contour Detection Method

Motion Detection using Frame Subtraction and Contour Detection Method

ABSTRACT: This paper describes the idea of motion detection using camera by the method of frame subtraction and contour detection. In the traditional recording system, the camera keeps recording day and night, even records the idle screen time where there is no movement or activity at all. This cause large wastage of storage and increases search time. Our system is designed to detect and track any moving event in a frame automatically. We are proposing a system based on background subtraction and contour detection to detect motion. The method that we are using in our project is highly efficient because it saves a lot of memory as it records only those data that are meaningful.
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Clinical evaluation of motion and position sense in the upper extremities of the elderly using motion analysis system

Clinical evaluation of motion and position sense in the upper extremities of the elderly using motion analysis system

Abstract: The purpose of this study was to measure kinesthetic accuracy in healthy older adults by using arm position and motion matching tests. We investigated the effect of task type, joint angle, and matching arm results on kinesthetic accuracy in the upper extremities of 17 healthy right-handed older adults. Blinded subjects were asked to match positions and motions at four reference joint angles: 1) shoulder flexion, 0°–60°; 2) elbow flexion, 90°–135°; 3) wrist extension, 0°–50° in the sagittal plane; and 4) shoulder abduction, 0°–60° in the frontal plane. The absolute difference in angular displacement between the reference and matching arms was calculated to determine kinesthetic accuracy. Results showed that subjects were more accurate at matching motion than position tasks (P=0.03). Shoulder and elbow joints were more sensitive than wrist joints in perceiving passive positions and motions (P0.05). The effect of the matching arm was found only when matching the joint angles of shoulder abduction and wrist extension (P0.01). These results are comparable to findings of other studies that used machine-generated kinesthetic stimuli. The manual measurement of kinesthetic accuracy could be effective as a preliminary screening tool for therapists in clinical settings.
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Fall Detection System using Accelerometer Principals with Arduino Development Board

Fall Detection System using Accelerometer Principals with Arduino Development Board

Marker less computer vision technique is planned to follow normal elements on the individual’s body surface . This method implements the approximation of rotation; scaling and translation, by means of a maximum possibility come near to carried out in the Gauss–Laguerre transform domain [4]. Mostly this approach is suitable for person movement analysis in hospitals contexts, where kinematics is performed by means of marker-based systems. For performing marker less human motion analysis GLT-based motion estimation method is incorporated to present a novel method. In this paper STS (sit to stand) task has been chosen for marker less analysis. STS is a general functional activity performed daily life. The main rotations associated with the STS movement mainly involve the sagittal plane, where ankle plantar flexion and dorsiflexion and hip and knee flexion–extensions can be observed. The estimation obtained from hip and ankle flexion–extension trajectories, the resultant angular velocities, and the task duration, it is possible to identify and quantify differences in the strategy between young people compared with the elder people. In this case results introducing the marker less motion capture based on the GLT algorithm as a suitable and feasible way out for the kinematic study of STS tasks.
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Robust Design of Pulse Oximeter Using Dynamic Control and Motion Artifact Detection Algorithms

Robust Design of Pulse Oximeter Using Dynamic Control and Motion Artifact Detection Algorithms

the NICU environment were capabilities of functioning reliably even under low perfusion, various transmission rates depending on individuals, and different intensities of ambient light. Therefore, an adaptive feedback system was implemented. Our SNR target was higher than 60 dB. First, the electrical cables for the photo diode and signal lines were electrically shielded. The setting of the IV converter gain was checked and tuned until better SNR values were obtained. The gain of the IV converter was set to 13 and that of AC amplifier was 39 (Fig. 1). To determine whether the SNR satisfied the design requirements, a SpO 2 simulator was used as a signal source.
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Modeling and Analysis of Monolithic Tri-Axial Ring Laser Gyro

Modeling and Analysis of Monolithic Tri-Axial Ring Laser Gyro

A certain rate of rotation of gyro induces a small difference between the time it takes light to traverse the ring in the two directions according to the Sagnac effect. This introduces a tiny separation between the frequencies of the counter-propagating beams, a motion of the standing wave pattern within the ring, and thus a beat pattern when those two beams are interfered outside the ring. Therefore the net shift of that interference pattern follows the rotation of the unit in the plane of the ring [4].RLGs, while more accurate than mechanical gyroscopes, and suffer from an effect known as "lock-in" at very slow rotation rates. When the ring laser is hardly rotating, the frequencies of the counter-propagating laser modes become almost identical.
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Falls classification using tri axial accelerometers during the five times sit to stand test

Falls classification using tri axial accelerometers during the five times sit to stand test

The  optimal  cut-­‐off  time  for  Model  2  was  16.86  s  for  this  cohort.  The  previously   suggested  cut-­‐off  of  15  s  [7]  resulted  in  reduced  classification  performance  for   the  present  cohort.  Model  2  was  more  specific  (75%  vs.  65%)  but  less  sensitive   (42%  vs.  55%)  compared  to  the  results  of  Buatois  et  al.  [7].  This  may  be  due  to   differences  in  study  design,  Buatois  et  al.  reported  a  longitudinal  study  and  used   FTSS  time  to  predict  recurrent  fallers,  whereas  the  current  cross-­‐sectional  study   classified  participants  based  on  retrospective  falls  status,  including  both  single   or  recurrent  falls  [7].  Additionally,  the  smaller  cohort  examined  in  this  study  may   be  too  small  to  replicate  previous  studies  of  2735  participants  [7].  However,   these  differing  cut-­‐offs  are  consistent  with  the  lack  of  consensus  in  falls  risk   thresholds  reported  in  the  literature  for  the  FTSS  [9],  emphasising  the  need  for  a   new,  more  objective  falls  risk  metric.  
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Theft Detection using Motion Sensing Camera

Theft Detection using Motion Sensing Camera

The system will capture images only when the motions exceed a certain threshold that is pre-set in the system. It thus reduces the volume of data that needs to be reviewed. Also, it will help to save data space by not capturing static images which usually do not contain the object of interest. It will be applicable to both office and home uses. After successfully implementing the project, it can be applied to the motion detection for a smart home security system which would be very much helpful in auto theft detection for security purpose. It can also be useful in bank, museum, and street at midnight. As a future work, we can introduce Artificial- Intelligence into the system to distinguish between real theft and just a simple movement of the object.
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Design Of Tri-Polarized Antenna

Design Of Tri-Polarized Antenna

Nowadays, people demands for high quality communication system such as high-quality video call, voice call and data. In order to achieve that, Multiple-Input Multiple-Output (MIMO) system is a must as conventional communication such as Single-Input Single-Output (SISO) communication system is incapable of providing high transfer speed and high capacity. In order to exploit the potential of MIMO system to maximum, polarization diversity method is preferred where multiple polarization antenna is used to overcome the mutual coupling problem among the huge number of antennas. In this project, a tri-polarized antenna that operate at frequency 2.4GHz with a dual circular polarization and a linear polarization is proposed. Circuit Simulation Tool (CST) software is used to design and construct the designed antenna. Investigation on single polarized antennas are carried out first where different feeding methods such as orthogonal feed are used to achieve circular and linear polarization. A dual circular polarized antenna is then designed by combining two single polarized antenna in a single antenna structure with two independent ports to generate dual polarization. The final stage of this project is the combination of the dual circular- polarized antenna and a linear polarized antenna in single antenna structure to realize tri-polarization.
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MOTION DETECTION ANALYSIS USING STATIC AND NOT STATIC IMAGES

MOTION DETECTION ANALYSIS USING STATIC AND NOT STATIC IMAGES

Abstract: Visual analysis of human motion is currently one of the most active research topics in computer vision. This strong interest is driven by a wide spectrum of promising applications in many areas such as virtual reality, smart surveillance, perceptual interface, etc. Human motion analysis concerns the detection, tracking and recognition of people, and more generally, the understanding of human behaviors, from image sequences involving humans. It provides a comprehensive survey of research on computer vision based human motion analysis. The emphasis is on three major issues involved in a general human motion analysis system, namely human detection, tracking and activity understanding. Various methods for each issue are discussed in order to examine the state of the art.
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Surveillance of Object Motion Detection and Alert Using Android

Surveillance of Object Motion Detection and Alert Using Android

Remote video surveillance and mobile monitoring so favorable is because that they both fit within your busy schedule. Remote monitoring and mobile surveillance give you on-the-go, real time access to your live camera view so you can check up on your property anytime day or night. These remote solutions made by the IP camera. Object detection in video is the basis for a number of important applications such as real time surveillance and visual tracking. For performance evaluation, we have implemented and evaluated our methodology. In the experiments performed both in indoor and outdoor environments, our approach considerably reduces the detection delay wile effectively handling random noise. The capability of this system extends to detecting foreground objects under all reasonable lighting conditions, tracking moving objects as they move along their trajectories, measuring the performance of the application as opposed to the ground truth of the video, handling occlusions and noises, projecting the object separated from its background.
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An Internet of Things Approach for Motion Detection Using ARM7

An Internet of Things Approach for Motion Detection Using ARM7

The ARM7TDMI-S is a broadly useful 32-bit chip, which offers superior and low power utilization. The ARM design depends on Reduced Instruction Set Computer (RISC) standards, and the direction set and related disentangle system are substantially less difficult than those of small scale modified Complex Instruction Set Computers. This straightforwardness brings about a high guideline throughput and amazing ongoing intrude on reaction from a little and savvy processor center. Pipeline methods are utilized with the goal that all parts of the handling and memory frameworks can work ceaselessly. Regularly, while one guideline is being executed, its success or is being decoded, and a third direction is being go ten from memory.
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Motion Detection Using IoT and Embedded System Concepts

Motion Detection Using IoT and Embedded System Concepts

Step 1: The system is initialized and configured. The software of this project includes modules such as Videoing module, Motion detection module, alerting module, networking module, Web server module and actuators module. These modules are included just to recognize whether the original user is using the system or an intruder is trying to use.

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Object Motion Detection Using Background Matching Framework

Object Motion Detection Using Background Matching Framework

Model the values of a particular pixel as a mixture of Gaussian distributions. Multiple adaptive Gaussians are necessary to cope with acquisition noise, lighting changes, and other natural occurrence. Pixel values that do not fit the background distributions are considered foreground.[8] This is a common method for real-time segmentation of moving regions in image sequences. Model Gaussians are updated using K-means approximation method. Each Gaussian distribution is assigned to represent the background or a moving object in the adaptive mixture model. Every pixel is then evaluated and classified as a moving region or as a background.[9]
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Piezoelectric Sensing Application Focused On Accelerometer Design

Piezoelectric Sensing Application Focused On Accelerometer Design

Accelerometer is an electronic device used to measure the activity of vibration and shock which present in all areas of our daily lives. They may be generated and transmitted by motors, turbines, machine-tools etc. In this project, a low cost accelerometer device is developed for the use of measuring vibration level from vibration sources such as motor engine, machineries with a simple set-up using piezoelectric cantilever. The accelerometer is developed using easily available piezoelectric materials with physical area about a few cm 2 (3cm x 5cm) which can easily mounted in the form of a cantilever. The piezoelectric cantilever was obtained off-the-shelf and tailor made to suit to the application as an accelerometer. The accelerometer was designed to operate at frequency higher than its resonant frequency so that a linear response would be produced. At this said frequency, the voltage output is proportional to the magnitude of the acceleration level (g-level), therefore the level of the vibration from any sources with excitation frequency higher than the piezoelectric cantilever structure natural frequency can be measured. However, at frequency range outside from resonant, the voltage output produced by the piezoelectric accelerometer is small and very difficult to measure accurately due to measurement noise. Therefore, amplifier circuit was developed to amplifier the small signal from the accelerometer before being measured and analyzed.
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