Development of a wearable wireless sensor network
The use of Wireless Sensor Networks (WSN) for monitoring of arm and walking motion is considered in this thesis to provide useful information in applications such as rehabilitation, sports science, military training, gaming and virtual reality. In this study, a wearable wireless sensor network using...
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| Format: | Thesis |
| Language: | English |
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2009
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| Online Access: | http://hdl.handle.net/10356/18781 |
| _version_ | 1826129015688134656 |
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| author | Tawfiq Taher. |
| author2 | Low Kay Soon |
| author_facet | Low Kay Soon Tawfiq Taher. |
| author_sort | Tawfiq Taher. |
| collection | NTU |
| description | The use of Wireless Sensor Networks (WSN) for monitoring of arm and walking motion is considered in this thesis to provide useful information in applications such as rehabilitation, sports science, military training, gaming and virtual reality. In this study, a wearable wireless sensor network using accelerometers has been developed to determine the motion of the arm in the sagittal plane. The uses of lightweight sensor nodes allow easy attachment to the limbs and pose little hindrance to natural movements yielding unrestrained measurements. The developed system is also low cost compared to sophisticated visual tracking systems with multiple cameras. Its low power consumption also allows for long term monitoring of arm motion.
In this system, the Microchip’s MiWi wireless networking protocol based on the IEEE802.15.4 specification has been used. The system consists of a number of sensor nodes that communicates wirelessly to the coordinator in a star network configuration. The coordinator sends the aggregated data to a personal computer via a serial communication. Each sensor node has on board accelerometer which is used to detect the tilt angle up to a 1 axes solution. During operation, the accelerometer on each sensor node measures the 3-axes acceleration in analog values. The information is then passed to the microcontroller that will perform analog-to-digital conversion through its built in ADCs. The values are then transmitted wirelessly using the RF transceiver to the coordinator. The real time algorithm execution, data acquisition and analysis process are performed using the computer.
In this thesis, the data packet capture process is conducted through a wireless packet analyzer. These data helped to understand the communication process. The accuracy of the system has been evaluated experimentally using a piezoelectric motor. The piezoelectric motor used for the experiment can be controlled to a 200 nano meter resolution. Various experiments have also been conducted to observe the performance of the collected data at different angular velocities. The performance test has also been conducted on a human subject. This is done with the hand swinging at different angular velocities with the sensor node attached to the arm. Experiment with a human subject walking at different velocities with the sensor nodes attached to the leg has also been conducted. The accuracy of the system in tracking the rotational angles of the upper and lower limb with two degrees of freedom has been determined. Form these experiments, it is found that error is about 4◦ to 5◦. |
| first_indexed | 2024-10-01T07:34:17Z |
| format | Thesis |
| id | ntu-10356/18781 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:34:17Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | ntu-10356/187812023-07-04T16:01:11Z Development of a wearable wireless sensor network Tawfiq Taher. Low Kay Soon School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems The use of Wireless Sensor Networks (WSN) for monitoring of arm and walking motion is considered in this thesis to provide useful information in applications such as rehabilitation, sports science, military training, gaming and virtual reality. In this study, a wearable wireless sensor network using accelerometers has been developed to determine the motion of the arm in the sagittal plane. The uses of lightweight sensor nodes allow easy attachment to the limbs and pose little hindrance to natural movements yielding unrestrained measurements. The developed system is also low cost compared to sophisticated visual tracking systems with multiple cameras. Its low power consumption also allows for long term monitoring of arm motion. In this system, the Microchip’s MiWi wireless networking protocol based on the IEEE802.15.4 specification has been used. The system consists of a number of sensor nodes that communicates wirelessly to the coordinator in a star network configuration. The coordinator sends the aggregated data to a personal computer via a serial communication. Each sensor node has on board accelerometer which is used to detect the tilt angle up to a 1 axes solution. During operation, the accelerometer on each sensor node measures the 3-axes acceleration in analog values. The information is then passed to the microcontroller that will perform analog-to-digital conversion through its built in ADCs. The values are then transmitted wirelessly using the RF transceiver to the coordinator. The real time algorithm execution, data acquisition and analysis process are performed using the computer. In this thesis, the data packet capture process is conducted through a wireless packet analyzer. These data helped to understand the communication process. The accuracy of the system has been evaluated experimentally using a piezoelectric motor. The piezoelectric motor used for the experiment can be controlled to a 200 nano meter resolution. Various experiments have also been conducted to observe the performance of the collected data at different angular velocities. The performance test has also been conducted on a human subject. This is done with the hand swinging at different angular velocities with the sensor node attached to the arm. Experiment with a human subject walking at different velocities with the sensor nodes attached to the leg has also been conducted. The accuracy of the system in tracking the rotational angles of the upper and lower limb with two degrees of freedom has been determined. Form these experiments, it is found that error is about 4◦ to 5◦. Master of Science (Computer Control and Automation) 2009-07-17T08:29:18Z 2009-07-17T08:29:18Z 2008 2008 Thesis http://hdl.handle.net/10356/18781 en 121 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems Tawfiq Taher. Development of a wearable wireless sensor network |
| title | Development of a wearable wireless sensor network |
| title_full | Development of a wearable wireless sensor network |
| title_fullStr | Development of a wearable wireless sensor network |
| title_full_unstemmed | Development of a wearable wireless sensor network |
| title_short | Development of a wearable wireless sensor network |
| title_sort | development of a wearable wireless sensor network |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems |
| url | http://hdl.handle.net/10356/18781 |
| work_keys_str_mv | AT tawfiqtaher developmentofawearablewirelesssensornetwork |