Development on wireless IMU sensors for biomechanical assessments

Measuring human movement and posture is an important area of research for biomedical engineering and rehabilitation. These measurements can be used to evaluate functional performance under normal and abnormal conditions and aid in clinical assessment. An increasingly popular method to measure human kinematics is by placing sensors known as Inertial Measurement Units (IMUs) at specific locations on the body to measure the motion of interest. These sensors measure acceleration and angular momentum, which can be used to assess human kinematics. Today it is also common for these devices to incorporate wireless technology such as the increasingly ubiquitous Bluetooth technology into their system, making it even easier to set up and start measuring without the need for cumbersome cables. The objective of this thesis was to assess the viability of re-purposing the NeckSmart v2 wireless IMUs in development by NeckCare, for use beyond their initial purpose of measuring and analyzing neck mobility. This was done by modifying the IMUs and implementing a multi-sensor wireless network to measure other kinematics. With the focus being on measuring flexion/extension of the knee. An analysis had to be made on what inertial data would be required to make these types of measurements. Adjustments were then made to the embedded software of the sensors to be able to wirelessly send required data with sufficient throughput. Software was also created to concurrently communicate with the sensors and take read the measurements from two or more wireless IMUs at the same time. The modifications made to the sensors were then validated by using them to measure the kinematics of the knee during gait.

Author dc:creator

• Adriaan Ólafur Árnason 1993-

Contributors dc:contributor

• Háskólinn í Reykjavík

• Hátækniverkfræði
• Meistaraprófsritgerðir
• Hreyfingar (líffræði)
• Mælingar
• Þráðlaust net
• Hné
• Hreyfifærni
• Mechatronics engineering
• Kinesiology--Research
• Measurement
• Wireless sensor networks
• Knee
• Flexure--Testing

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/1946/42095

OAI identifier oai:identifier

oai:skemman.is:1946/42095