First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Communication in Smoking Cessation and Self-management : a study at Nurse-led COPD-clinics in Primary Health Care

ABSTRACTThe general aim of this thesis was to investigate behavioral change communication at nurse-led chronic obstructive pulmonary disease (COPD) clinics in primary health care, focusing on communication in self-management and smoking cessation for patients with COPD.Designs: Observational, prospective observational and experimental designs were used.Methods: To explore and describe the structure and content of self-management education and smoking cessation communication, consultations between patients (n=30) and nurses (n=7) were videotaped and analyzed with three instruments: Consulting Map (CM), the Motivational Interviewing Treatment Integrity (MITI) scale and the Client Language Assessment in Motivational Interviewing (CLAMI). To examine the effects of structured self-management education, patients with COPD (n=52) were randomized in an intervention and a control group. Patients’ quality of life (QoL), knowledge about COPD and smoking cessation were examined with a questionnaire on knowledge about COPD and smoking habits and with St. George’s Respiratory Questionnaire, addressing QoL. Results: The findings from the videotaped consultations showed that communication about the reasons for consultation mainly concerned medical and physical problems and (to a certain extent) patients´ perceptions. Two consultations ended with shared understanding, but none of the patients received an individual treatment-plan. In the smoking cessation communication the nurses did only to a small extent evoke patients’ reasons for change, fostered collaboration and supported patients’ autonomy. The nurses provided a lot of information (42%), asked closed (21%) rather than open questions (3%), made simpler (14%) rather than complex (2%) reflections and used MI non-adherent (16%) rather than MI-adherent (5%) behavior. Most of the patients’ utterances in the communication were neutral either toward or away from smoking cessation (59%), utterances about reason (desire, ability and need) were 40%, taking steps 1% and commitment to stop smoking 0%. The number of patients who stopped smoking, and patients’ knowledge about the disease and their QoL, was increased by structured self-management education and smoking cessation in collaboration between the patient, nurse and physician and, when necessary, a physiotherapist, a dietician, an occupational therapist and/or a medical social worker.Conclusion The communication at nurse-led COPD clinics rarely involved the patients in shared understanding and responsibility and concerned patients’ fears, worries and problems only to a limited extent. The results also showed that nurses had difficulties in attaining proficiency in behavioral change communication. Structured self-management education showed positive effects on patients’ perceived QoL, on the number of patients who quit smoking and on patients’ knowledge about COPD.

Nurses’ and patients’ communication in smoking cessation at nurse-led COPD clinics in primary health care

Background: Smokers with chronic obstructive pulmonary disease (COPD) have high nicotine dependence making it difficult to quit smoking. Motivational interviewing (MI) is a method that is used in stimulating motivation and behavioral changes. Objective: To describe smoking cessation communication between patients and registered nurses trained in MI in COPD nurse-led clinics in Swedish primary health care. Methods: A prospective observational study with structured quantitative content analyses of the communication between six nurses with basic education in MI and 13 patients in non-smoking consultations. Results: Only to a small extent did nurses’ evoke patients’ reasons for change, stimulate collaboration, and support patients’ autonomy. Nurses provided information, asked closed questions, and made simple reflections. Patients’ communicationwasmainly neutral and focusing on reasons for and against smoking. It was uncommon for patients to be committed and take steps toward smoking cessation. Conclusion: The nurses did not adhere to the principles of MI in smoking cessation, and the patients focused to a limited extent on how to quit smoking. Practice implications: To make patients more active, the nurses need more education and continuous training in motivational communication.