A sensor system to detect events in gait for the correction of abnormalities in neurological patients

Abdul Malik, Noreha (2010) A sensor system to detect events in gait for the correction of abnormalities in neurological patients. University of Southampton, Faculty of Physical and Applied Sciences, Doctoral Thesis , 401pp.


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Contraction of the hamstrings or gluteals muscles, using electrical stimulation, could improve the abnormal gait in neurological patients. The stimulation timing which follows the normal muscle activity is impractical to achieve using the traditional sensor (the footswitch). This study focuses on the development of a new sensor system for the detection of events in the gait cycle to trigger stimulation of hamstrings or gluteals muscles for preventing knee hyperextension into early stance or reducing the excessive hip flexion/adduction at heel strike. A sensor unit, consisting of four accelerometers,has been designed to determine the angles and linear accelerations of a segment without the need for integration. Tests have been carried out to verify the error of the sensor unit angle measurement by comparing it with the output from a potentiometer of a simple inverted pendulum. In five healthy subjects during walking, assessments have been carried out to compare the segment angle of the thigh, shank and foot calculated from the sensor unit, with the same angles measured using a motion capture system (ViconTM). The results show that the shank segment angles have a similar pattern. A sensor system to detect gait events has been developed. It consists of the sensor unit, a correlation coefficient calculation and a set of rules with thresholds. The system has detected reliably all heel strikes and a place in the gait cycle representing the tibia vertical position of five healthy subjects. Two sample windows selected from one set of the subject data have been used to detect all of the events. Using the same system, all tibial vertical events have been detected reliably compared to the footswitch in six neurological patients. In five patients, the same sample window, selected from the healthy subject, was used in the detection. For one patient, a sample window selected from the same patient data was used. Further work will be needed to implement the system in real time and evaluate it’s use with electrical stimulation as well as to establish the effect of stimulation in patients using the sensor unit as the trigger

Item Type: Thesis (Doctoral)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions : Faculty of Physical Sciences and Engineering > Electronics and Computer Science > EEE
ePrint ID: 196615
Accepted Date and Publication Date:
October 2010Made publicly available
Date Deposited: 09 Sep 2011 10:06
Last Modified: 30 Jun 2014 23:03
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/196615

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