Vinsamlegast notið þetta auðkenni þegar þið vitnið til verksins eða tengið í það: https://hdl.handle.net/1946/46281
Incorrect posture and improper technique during physical activity, whether in sports, work, everyday life, or as a result of prior injuries, can result in a higher risk of future injury and a decline in performance. Kiso aims to equip its product, KMU3, with the capability of detecting improper form and muscle usage in its users. The goal is to enhance athletic performance, correct posture and form in daily activities, and aid in the recovery and overall improvement of life for
those, post-injury. Currently, Kiso uses EMG sensors to measure muscle activity, such as activation time and deactivation time. What they require is the ability to record and monitor the position, speed, acceleration, and orientation of desired body parts. Combining the currently used EMG sensors with IMU sensors allows Kisos KMU3 to track the patients movement and position, and combine it with
the data from the patients muscles, provided by the EMG. This provides a deeper understanding of the mechanics behind the patients movement and is a big improvement over current measurement capabilities, which could result in a more precise and accurate diagnosis.
Potential scenarios where the value of adding the IMU sensors can be seen is to measure the range of motion of an individual during certain exercises, detect over- / under-trained muscles, and monitor the effectiveness of an individuals re-habilitation or training, just to name a few. On an academic level, this is a topic of
research in fields such as control systems, robotics, and navigation where an accurate and robust angle estimation is a valuable resource. In applied/industry, angle estimation is used in a variety of applications such as robotics, virtual and augmented reality systems, wearable devices, and other applications in the aerospace, gaming, and consumer electronics industries.
In order for the IMU data to provide valuable information about the subjects limb orientation it was decided that the angle estimation error from the IMU should remain within ±10◦. The specific investigation addressed in this thesis proposal is therefore to use sensor fusion, vector, and geometry calculations to calculate the orientation of an IMU with an error of less than ±10◦.
Using three independent Kalman filters, one for each distinct Euler angle calculation, this goal was achieved for the roll and pitch angle estimations errors as they were each under ±5◦. However the goal could not be achieved for the yaw angle estimation error which would regularly hover around ±20◦ due to external factors effecting the magnetometer readings.
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Arons_Masters_Thesis_skemman.pdf | 2.78 MB | Lokaður til...28.02.2027 | Heildartexti | ||
aronis_umsokn_a_lokun_verkefnis.pdf | 435.5 kB | Opinn | Beiðni um lokun | Skoða/Opna |