Multiple Sclerosis (MS) is a chronic inflammatory disease of the central nervous system. It affects approximately 400.000 individuals in Europe and about 2.5 million worldwide. Clinical symptoms of MS are highly variable and depend on the localization of lesions in the brain and spinal cord. Patients with chronic progressive neurological diseases such as MS typically show a decrease of physical activity as compared with healthy individuals. Approximately 75 to 80 percent of patients with MS (PwMS) experience walking and physical activity impairment in early stages of the disease. Therefore, walking impairment is considered as a hallmark symptom as this may have a significant impact on different daily activities. Moreover, an indirect association between overall MS symptoms and physical activity was found.
Several studies investigated the walking ability and physical activity under free-living conditions in PwMS, as this may provide significant information to predict the patient’s health status. Different methods have been used for this purpose, including subjective approaches like self-report, questionnaires or diary methods. Altho ... mehrugh these methods are inexpensive and can easily be employed preferably in large scale studies, they are prone to error due to memory failure and other kind of misreporting. For many years, laboratory analysis systems have been considered to be the “gold standard” for physical activity and walking ability assessment. Nevertheless, these methods require extensive technical support and are unable to assess unconstrained physical activities in free-living situations. Thus, there is increasing interest in ambulatory assessment methods that provide objective measures of physical activity and gait parameters.
Therefore, this thesis takes a different approach and investigate the usage of an objective monitoring system to early detect the slightly changes in disease-related walking ability and gait abnormality using one accelerometer. Moreover, this work aims to classify the derived acceleration data regarding their response to a certain intervention and treatment. In doing so, first of all, different algorithms were developed to extract activity and gait parameters in time, frequency and time-frequency domain. Then a Home-based system was developed and provided to help doctors monitor the changes in the ambulatory physical activity of PwMS objectively. The developed system was applied in two different studies over long period of time (one year) to assess changes in physical activity and gait behavior of PwMS and to classify their response to medical treatment.
The aim of the first study was to investigate the ability of the developed parameters to objectively capture the changes in motor and walking ability in PwMS. Moreover, the objective was to provide additional evidence from long-term design study that support the association between changes in physical activity and walking ability and disease progression over time.
The aim of the second study was to investigate the effectiveness of the medication treatment using the developed gait parameters and the assessment system developed in this work. The result of the study was compared to those assessed in the clinic. Comprehensive analysis of gait features in frequency and time-frequency domain can provide complementary information to understand gait patterns. Therefore, in this study, the parameters peak frequency and energy concentration were integrated along with time-domain parameters, such as step counts and walking speed.
In case of chronic diseases, such as MS, medical benefit is the main factor to accept new technology. Thus, the developed system should be advantageous for diagnosis and therapy of MS. Moreover, it is important for the physician to be able to get better overview of the medical data about the disease course and health condition of their patients. Therefore, many critical factors regarding medical, technical and user specific aspects were considered in this work while developing the ambulatory assessment system. To assess the acceptance of the system a questionnaire was designed with main focus on two factors; usefulness and ease-of-use. The questionnaire was based on the Technology Acceptance Model (TAM).
As a result, the design, validation and clinical application of Home-based monitoring system and algorithmic methods developed in this thesis offer the opportunity to comprehensively and objectively assess the pattern of behavioral change in physical activity and walking ability using one sensor across prolonged periods of time. The derived information may assist in the process of clinical decision making in the context of neurological rehabilitation and intervention (evaluation of medication or physiotherapy effects) and thus help to eventually improve the patients’ quality of life.
In this work the focus was on patients with multiple sclerosis, however the developed and evaluated system can be adapted to other chronic diseases with physical activity disorders and impairment of gait.