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An artificially-intelligent biomeasurement system for total hip arthroplasty patient rehabilitation.

Law, Ewan James


Ewan James Law


Christopher Macleod


This study concerned the development and validation of a hardware and software biomeasurement system, which was designed to be used by physiotherapists, general practitioners and other healthcare professionals. The purpose of the system is to detect and assess gait deviation in the form of reduced post-operative range of movement (ROM) of the replacement hip joint in total hip arthroplasty (THA) patients. In so doing, the following original work is presented: Production of a wearable, microcontroller-equipped system which was able to wirelessly relay accelerometer sensor data of the subjects key hip-position parameters to a host computer, which logs the data for later analysis. Development of an artificial neural network is also reported, which was produced to process the sensor data and output assessment of the subjects hip ROM in the flexion/extension and abduction/adduction rotations (forward and backward swing and outward and inward movement of the hip respectively). The review of literature in the area of biomeasurement devices is also presented. A major data collection was carried out using twenty-one THA patients, where the device output was compared to the output of a Vicon motion analysis system which is considered the gold standard in clinical gait analysis. The Vicon system was used to show that the device developed did not itself affect the patients hip, knee or ankle gait cycle parameters when in use, and produced measurement of hip flexion/extension and abduction/adduction closely approximating those of the Vicon system. In patients who had gait deviations manifesting in reduced ROM of these hip parameters, it was demonstrated that the device was able to detect and assess the severity of these excursions accurately. The results of the study substantiate that the system developed could be used as an aid for healthcare professionals in the following ways: 1) To objectively assess gait deviation in the form of reduced flexion/extension and abduction/adduction in the human hip, after replacement; 2) Monitoring of patient hip ROM post-operatively; 3) Assist in the planning of gait rehabilitation strategies related to these hip parameters.


LAW, E.J. 2012. An artificially-intelligent biomeasurement system for total hip arthroplasty patient rehabilitation. Robert Gordon University, PhD thesis.

Thesis Type Thesis
Deposit Date Jan 7, 2014
Publicly Available Date Jan 7, 2014
Keywords Bio measurement system; Total hip arthroplasty; Artificial neural network; Accelerometer; Physiotherapy; Gait analysis
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