Multimodal Classification of Parkinson's Disease in Home Environments with Resiliency to Missing Modalities

Parkinson’s disease (PD) is a chronic neurodegenerative condition that affects a patient’s everyday life. Authors have proposed that a machine learning and sensor-based approach that continuously monitors patients in naturalistic settings can provide constant evaluation of PD and objectively analyse its progression. In this paper, we make progress toward such PD evaluation by presenting a multimodal deep learning approach for discriminating between people with PD and without PD. Specifically, our proposed architecture, named MCPD-Net, uses two data modalities, acquired from vision and accelerometer sensors in a home environment to train variational autoencoder (VAE) models. These are modality-specific VAEs that predict effective representations of human movements to be fused and given to a classification module. During our end-to-end training, we minimise the difference between the latent spaces corresponding to the two data modalities. This makes our method capable of dealing with missing modalities during inference. We show that our proposed multimodal method outperforms unimodal and other multimodal approaches by an average increase in F1-score of 0.25 and 0.09, respectively, on a data set with real patients. We also show that our method still outperforms other approaches by an average increase in F1-score of 0.17 when a modality is missing during inference, demonstrating the benefit of training on multiple modalities

AI and Non AI Assessments for Dementia

Current progress in the artificial intelligence domain has led to the development of various types of AI-powered dementia assessments, which can be employed to identify patients at the early stage of dementia. It can revolutionize the dementia care settings. It is essential that the medical community be aware of various AI assessments and choose them considering their degrees of validity, efficiency, practicality, reliability, and accuracy concerning the early identification of patients with dementia (PwD). On the other hand, AI developers should be informed about various non-AI assessments as well as recently developed AI assessments. Thus, this paper, which can be readable by both clinicians and AI engineers, fills the gap in the literature in explaining the existing solutions for the recognition of dementia to clinicians, as well as the techniques used and the most widespread dementia datasets to AI engineers. It follows a review of papers on AI and non-AI assessments for dementia to provide valuable information about various dementia assessments for both the AI and medical communities. The discussion and conclusion highlight the most prominent research directions and the maturity of existing solutions.Comment: 49 page

Objective assessment of upper limb motor symptoms in Parkinson's Disease using body-worn sensors

MD ThesisBackground There is a need for an objective method of symptom assessment in Parkinson's disease (PD) to enable better treatment decisions and to aid evaluation of new treatments. Current assessment methods; patient-completed symptom diaries and clinical rating scales, have limitations. Accelerometers (sensors capable of capturing data on human movement) and analysis using artificial neural networks (ANNs) have shown potential as a method of motor symptom evaluation in PD. It is unknown whether symptom monitoring with body-worn sensors is acceptable to PD patients due to a lack of previous research. Methods 34 participants with PD wore bilateral wrist-worn accelerometers for 4 hours in a research facility (phase 1) and then for 7 days in their homes (phase 2) whilst also completing symptom diaries. An ANN designed to predict a patient’s motor status, was developed and trained based on accelerometer data during phase 2. ANN performance was evaluated (leave-one-out approach) against patient-completed symptom diaries during phase 2, and against clinician rating of disease state during phase 1 observations. Participants’ views regarding the sensors were obtained via a Likert-style questionnaire completed after each phase. Differences in responses between phases were assessed for using the Wilcoxon rank-sum test. Results ANN-derived values of the proportion of time in each disease state (phase 2), showed strong, significant correlations with values derived from patient-completed symptom diaries. ANN disease state recognition during phase 1 was sub-optimal. High concordance with sensors was seen. Prolonged wearing of the sensors did not adversely affect participants’ opinions on the wearability of the sensors, when compared to their responses following phase 1 Conclusions Accelerometers and ANNs produced results comparable to those of symptom diaries. Our findings suggest that long-term monitoring with wrist-worn sensors is acceptable to PD patients

Fall Prevention Using Linear and Nonlinear Analyses and Perturbation Training Intervention

abstract: Injuries and death associated with fall incidences pose a significant burden to society, both in terms of human suffering and economic losses. The main aim of this dissertation is to study approaches that can reduce the risk of falls. One major subset of falls is falls due to neurodegenerative disorders such as Parkinson’s disease (PD). Freezing of gait (FOG) is a major cause of falls in this population. Therefore, a new FOG detection method using wavelet transform technique employing optimal sampling window size, update time, and sensor placements for identification of FOG events is created and validated in this dissertation. Another approach to reduce the risk of falls in PD patients is to correctly diagnose PD motor subtypes. PD can be further divided into two subtypes based on clinical features: tremor dominant (TD), and postural instability and gait difficulty (PIGD). PIGD subtype can place PD patients at a higher risk for falls compared to TD patients and, they have worse postural control in comparison to TD patients. Accordingly, correctly diagnosing subtypes can help caregivers to initiate early amenable interventions to reduce the risk of falls in PIGD patients. As such, a method using the standing center-of-pressure time series data has been developed to identify PD motor subtypes in this dissertation. Finally, an intervention method to improve dynamic stability was tested and validated. Unexpected perturbation-based training (PBT) is an intervention method which has shown promising results in regard to improving balance and reducing falls. Although PBT has shown promising results, the efficacy of such interventions is not well understood and evaluated. In other words, there is paucity of data revealing the effects of PBT on improving dynamic stability of walking and flexible gait adaptability. Therefore, the effects of three types of perturbation methods on improving dynamics stability was assessed. Treadmill delivered translational perturbations training improved dynamic stability, and adaptability of locomotor system in resisting perturbations while walking.Dissertation/ThesisDoctoral Dissertation Biomedical Engineering 201

Objective evaluation of Parkinson's disease bradykinesia

Bradykinesia is the fundamental motor feature of Parkinson’s disease - obligatory for diagnosis and central to monitoring. It is a complex clinicalsign that describes movements with slow speed, small amplitude, irregular rhythm, brief pauses and progressive decrements. Clinical ascertainment of the presence and severity of bradykinesia relies on subjective interpretation of these components, with considerable variability amongst clinicians, and this may contribute to diagnostic error and inaccurate monitoring in Parkinson’s disease. The primary aim of this thesis was to assess whether a novel non-invasive device could objectively measure bradykinesia and predict diagnostic classification of movement data from Parkinson’s disease patients and healthy controls. The second aim was to evaluate how objective measures of bradykinesia correlate with clinical measures of bradykinesia severity. The third aim was to investigate the characteristic kinematic features of bradykinesia. Forty-nine patients with Parkinson’s disease and 41 healthy controls were recruited in Leeds. They performed a repetitive finger-tapping task for 30 seconds whilst wearing small electromagnetic tracking sensors on their finger and thumb. Movement data was analysed using two different methods - statistical measures of the separable components of bradykinesia and a computer science technique called evolutionary algorithms. Validation data collected independently from 13 patients and nine healthy controls in San Francisco was used to assess whether the results generalised. The evolutionary algorithm technique was slightly superior at classifying the movement data into the correct diagnostic groups, especially for the mildest clinical grades of bradykinesia, and they generalised to the independent group data. The objective measures of finger tapping correlated well with clinical grades of bradykinesia severity. Detailed analysis of the data suggests that a defining feature of Parkinson’s disease bradykinesia called the sequence effect may be a physiological rather than a pathological phenomenon. The results inform the development of a device that may support clinical diagnosis and monitoring of Parkinson’s disease and also be used to investigate bradykinesia

Automated Intelligent Cueing Device to Improve Ambient Gait Behaviors for Patients with Parkinson\u27s Disease

Freezing of gait (FoG) is a common motor dysfunction in individuals with Parkinson’s disease (PD). FoG impairs walking and is associated with increased fall risk. Although pharmacological treatments have shown promise during ON-medication periods, FoG remains difficult to treat during medication OFF state and in advanced stages of the disease. External cueing therapy in the forms of visual, auditory, and vibrotactile, has been effective in treating gait deviations. Intelligent (or on-demand) cueing devices are novel systems that analyze gait patterns in real-time and activate cues only at moments when specific gait alterations are detected. In this study we developed methods to analyze gait signals collected through wearable sensors and accurately identify FoG episodes. We also investigated the potential of predicting the symptoms before their actual occurrence. We collected data from seven participants with PD using two Inertial Measurement Units (IMUs) on ankles. In our first study, we extracted engineered features from the signals and used machine learning (ML) methods to identify FoG episodes. We tested the performance of models using patient-dependent and patient-independent paradigms. The former models achieved 92.5% and 89.0% for average sensitivity and specificity, respectively. However, the conventional binary classification methods fail to accurately classify data if only data from normal gait periods are available. In order to identify FoG episodes in participants who did not freeze during data collection sessions, we developed a Deep Gait Anomaly Detector (DGAD) to identify anomalies (i.e., FoG) in the signals. DGAD was formed of convolutional layers and trained to automatically learn features from signals. The convolutional layers are followed by fully connected layers to reduce the dimensions of the features. A k-nearest neighbors (kNN) classifier is then used to classify the data as normal or FoG. The models identified 87.4% of FoG onsets, with 21.9% being predicted on average for each participant. This study demonstrates our algorithm\u27s potential for delivery of preventive cues. The DGAD algorithm was then implemented in an Android application to monitor gait patterns of PD patients in ambient environments. The phone triggered vibrotactile and auditory cues on a connected smartwatch if an FoG episode was identified. A 6-week in-home study showed the potentials for effective treatment of FoG severity in ambient environments using intelligent cueing devices

Designing a comprehensive system for analysis of handwriting biomechanics in relation to neuromotor control of handwriting

A comprehensive system for investigation of biomechanical and neuromuscular processes involved with producing handwriting and drawing was developed. The system included a pen-like grip measuring device that enabled the variations of finger grip force associated with writing and drawing to be measured while holding the pen in tripod grip. The pen was integrated with a digitiser tablet for recording x,ycoordinates and pressure of the nib and a motion analysis system for recording the limb and hand kinematics. It was observed that for line drawing in the y-direction of the tablet, finger forces were directly related to pen tip movement and finger forces were modulated in a repeatable and predictable fashion, while this was not the case for line drawing in the x-direction. This was evidence for longstanding assumptions. Wrist rotation was required for production of lines in the x-direction without excessive deviation. For writing tasks, it was observed that no two tasks performed by one subject share an identical writing process, not even when the writing results are (nearly) identical. The neuromuscular control apparatus is highly flexible and works in a coordinated fashion that allows production of nearly equal end-results by means of different mechanical and therefore neuromuscular processes. For spiral drawing, tremor that originates from the fingers, hand and arm was quantified with the transducer pen. Limb joint kinematics were displayed in three dimensions with colour coding of coordinate sample numbers. This method can reveal the origin of some forms of limb tremor. Pen grip force patterns during signature writing were found to be characteristic for subjects, which relate to their individual pen-hand interaction, resulting from fine control of distal joints. Variation between trials of the same subject was observed, revealing adaptations of the computational processes during writing. The potential for signature verification by means of finger force recording was explored.A comprehensive system for investigation of biomechanical and neuromuscular processes involved with producing handwriting and drawing was developed. The system included a pen-like grip measuring device that enabled the variations of finger grip force associated with writing and drawing to be measured while holding the pen in tripod grip. The pen was integrated with a digitiser tablet for recording x,ycoordinates and pressure of the nib and a motion analysis system for recording the limb and hand kinematics. It was observed that for line drawing in the y-direction of the tablet, finger forces were directly related to pen tip movement and finger forces were modulated in a repeatable and predictable fashion, while this was not the case for line drawing in the x-direction. This was evidence for longstanding assumptions. Wrist rotation was required for production of lines in the x-direction without excessive deviation. For writing tasks, it was observed that no two tasks performed by one subject share an identical writing process, not even when the writing results are (nearly) identical. The neuromuscular control apparatus is highly flexible and works in a coordinated fashion that allows production of nearly equal end-results by means of different mechanical and therefore neuromuscular processes. For spiral drawing, tremor that originates from the fingers, hand and arm was quantified with the transducer pen. Limb joint kinematics were displayed in three dimensions with colour coding of coordinate sample numbers. This method can reveal the origin of some forms of limb tremor. Pen grip force patterns during signature writing were found to be characteristic for subjects, which relate to their individual pen-hand interaction, resulting from fine control of distal joints. Variation between trials of the same subject was observed, revealing adaptations of the computational processes during writing. The potential for signature verification by means of finger force recording was explored

The Influence of Cerebellar Transcranial Direct Current Stimulation on Motor Function in Parkinson’s Disease

Parkinson\u27s disease (PD) is the most common movement disorder and the second most common neurodegenerative disorder. PD is characterized by dopaminergic cell loss in the substantia nigra pars compacta, which leads to a reduction in dopamine in the striatum. These physiological mechanisms lead to a number of motor impairments such as bradykinesia, rigidity, tremor, and postural instability that severely limit the ability of individuals with PD to perform many essential daily living activities. Although current pharmacological, surgical, and physical exercise treatment approaches are valuable they are either only mildly effective, expensive, or associated with a variety of side effects. Therefore, development of new adjunct interventions that are effective and have a realistic potential to be implemented into clinical practice would be highly beneficial. The current pharmaceutical, surgical, and management strategies for PD are directed towards relieving the symptoms associated with PD. Levodopa combined with other medications represents the standard treatment for PD, but their efficacy diminishes over time and leads to side effects such as dyskinesia. For advanced PD, deep brain stimulation is the established surgical approach and can improve motor function and quality of life. Nonetheless, deep brain stimulation is associated with surgical contraindications, high costs, neuropsychiatric side effects, and is not effective in treating non-motor PD symptoms. Physical exercise is also commonly prescribed in PD primarily based on animal studies, but the magnitude of these positive effects has generally not been achieved in humans. However, not all patients have the ability, financial resources, available facilities, or determination to engage in long-term high intensity exercise programs to realize their benefit. While several forms of exercise can induce clinically significant motor improvements in PD, the most successful strategy to improve motor function would likely entail pairing adjunctive therapies with rehabilitation to enhance or complement the effects of exercise. Non-invasive brain stimulation methods such as repetitive transcranial magnetic stimulation (rTMS) have shown promise in alleviating PD symptoms, but practical limitations as well as inconsistent or mild positive effects limit its clinical applicability. Recently, transcranial direct current stimulation (tDCS) has emerged as a powerful brain stimulation technique that can enhance motor performance and cortical function in PD. Most importantly, tDCS is now regarded to be a more effective form of non-invasive brain stimulation compared to rTMS in PD. In addition, tDCS offers several important advantages over rTMS such as portability, safety, ease of administration, ability to be delivered during motor activities, a superior ability to blind participants with SHAM stimulation, and low cost (as low as $400 versus$20,000-100,000 for rTMS). Taken together, these lines of reasoning strongly suggest that tDCS may represent such an intervention with a realistic potential to be translated into clinical practice. Anodal tDCS of motor cortex (M1) improves motor performance in young adults, older adults, stroke, and in PD. This involves passing a current over M1 through surface electrodes, which increases M1 excitability for ~90 minutes. Accordingly, most M1-tDCS studies have found improvements in motor performance of approximately 10-15% during or after a single 10-20 minute session when compared to motor practice alone in young adults and old adults as well as in PD. Most importantly, longer-term studies lasting between 3 days and 2 weeks have documented that these improvements in performance can be increased to up about 20-30% compared to a single M1-tDCS session in healthy adults and in one notable study in PD. Despite these positive findings involving M1-tDCS in PD, development of new non-invasive brain stimulation techniques or the targeting of additional brain areas could provide additional avenues to improve motor function in PD. Recently, tDCS delivered to the cerebellum (c-tDCS) has also been reported to significantly improve motor skill in young and old adults. The ability of c-tDCS to impact motor skill learning in older adults is particularly interesting because accumulating evidence suggests that the cerebellum may be the primary brain area responsible for the movement impairments often observed in by older adults. Similarly, the cerebellum has recently been implicated in contributing to the motor deficits associated with PD. Despite these observations, no studies have examined the influence of c-tDCS on motor learning in PD, given that most individuals with PD are older adults. The M1 projections to upper limb motor neurons play a predominant role in the generation and execution of skilled movements. However, M1 output depends on inputs from sources such as premotor cortex, contralateral M1, and basal ganglia along with crucial contributions from cerebellum, which is strongly involved in movement timing, multi-joint coordination, agonist and antagonist muscle interactions, and error detection in goal-directed movements. Although PD is primarily a basal ganglia disorder, the widespread cerebellar involvement in PD pathophysiology based on mounting anatomical, physiological, and clinical evidence forms the basis for targeting it with c-tDCS. In addition, more specific evidence provides further rationale for c-tDCS in PD treatment: 1) previously unknown bi-directional pathways have recently been discovered between basal ganglia and cerebellum and M1-tDCS has been shown in animal and human physiological studies to induce remote effects in anatomically interconnected CNS regions (basal ganglia, thalamus, pain centers, spinal cord). For example, M1-tDCS increased striatal extracellular dopamine levels in rats and improved their motor function. The evidence for tDCS remote effects provides support for the idea that c-tDCS may indirectly impact basal ganglia in PD; 2) impaired cerebellar function in PD may be a compensatory mechanism that attempts to diminish the negative influences of abnormal basal ganglia activity as PD patients with greater cerebellar activity exhibit better motor function. Thus, c-tDCS may improve function by enhancing these compensatory processes by increasing cerebellar activity; 3) c-tDCS improves motor performance in young and older adults and tDCS of M1 improves performance in these populations and in PD; 4) tDCS efficacy scales with age and impairment level due to motor disorders making improvements in PD more likely to occur; and 5) c-tDCS led to greater improvements in an arm movement task compared to M1-tDCS in young adults. Collectively, these factors and the positive effects on motor performance obtained in several studies involving c-tDCS in young and older adults provide strong rationale for the investigation of c-tDCS for PD treatment. Despite these interrelated lines of reasoning, no studies have examined the influence of c-tDCS on motor performance in PD in either the short or long-term. Therefore, the overall purpose of this dissertation was to determine the influence of c-tDCS on motor skill acquisition, motor learning, and transfer of motor learning in PD. This was accomplished through a series of 3 interrelated studies. For the first study (Chapter 2), the primary purpose was to examine the influence of a single session of c-tDCS on motor performance in a complex, visuomotor isometric precision grip task (PGT) in PD. The secondary purpose was to determine the influence of c-tDCS on the transfer of motor performance in PD. Based on c-tDCS studies involving practice of hand and arm tasks in young and older adults and M1-tDCS studies in PD, it was hypothesized that c-tDCS would increase motor performance in the PGT and in the transfer tasks to a greater extent than SHAM stimulation in PD. Therefore, the major methodological aspects of study 1 that distinguished it from the subsequent studies included: 1) it involved acute application of c-tDCS in a single experimental session; 2) it utilized only one primary motor task that was performed concurrently with administration of c-tDCS; 3) it also investigated the influence of c-tDCS on transfer of motor performance to motor tasks not performed simultaneously with c-tDCS and not practiced extensively; and 4) all experimental testing was conducted while participants were off of their medications; and 5) it utilized a within-participants design. Therefore each participant underwent both the c-tDCS and SHAM conditions. The within-participants design was chosen in this study as it has the advantage of being able to minimize the possible inter-individual response to c-tDCS. The main findings of the study were that a single session of c-tDCS did not elicit improvements in motor performance or transfer of motor performance in hand and arm tasks in PD In the second study (Chapter 3), the purpose was to determine the effects of c-tDCS on motor performance in PD while participants were on medications. This was accomplished by having participants perform two motor tasks with their most affected hand in a baseline condition and in an experimental condition. Most importantly, one group of participants received c-tDCS during performance of the motor tasks in the experimental condition, whereas the other group received SHAM stimulation. The major methodological features of study 2 that distinguished it in most aspects from the two other studies included: 1) it involved acute application of c-tDCS in a single experimental session; 2) it comprised two different motor tasks that were performed concurrently with administration of c-tDCS; 3) it did not investigate the influence of c-tDCS on transfer of motor performance to untrained tasks; 4) all experimental testing was conducted while participants were on their medications; 5) it utilized a between-participants design. Thus, two groups of PD participants were utilized and allocated into either a c-tDCS or SHAM group. The main findings of the study were that a single session of c-tDCS did not elicit enhancements in motor performance in either of the hand and arm tasks performed concurrent with c-tDCS in PD. In the third study (Chapter 4), the primary purpose was to determine the influence of long-term application of c-tDCS on motor learning in PD. The secondary purpose was to examine the influence of long-term application of c-tDCS on transfer of motor learning in PD. This was accomplished by employing a long-term training study. Specifically, 9 practice sessions were performed over a 2 week period that involved extensive practice of an isometric pinch grip task (PGT) and a rapid arm movement task (AMT). These practice tasks were performed over a 25 minute period concurrent with either c-tDCS or SHAM stimulation. A set of transfer tasks that included clinical rating scales, manual dexterity tests, and lower extremity function assessments were quantified in test sessions at Baseline, 1, 14, and 28 days after the end of practice (EOP). Thus, the major methodological features of study 3 that distinguished it in most aspects from the two other studies included: 1) it involved chronic application of c-tDCS over 9 practice sessions and was concerned with the effect of c-tDCS on long-term motor learning; 2) it comprised two different motor tasks that were performed concurrently with administration of c-tDCS; 3) it investigated the influence of c-tDCS on transfer of motor learning to untrained tasks; 4) experimental testing was conducted while participants were both off and on their medications; 5) it utilized a between-participants design. Thus, participants were allocated into either a c-tDCS or SHAM group. The main findings of the study were that long-term application of c-tDCS concurrent with motor practice did not enhance motor learning to a greater extent than practice alone in PD. Similarly, long-term application of c-tDCS did not increase transfer of motor learning in PD. In summary, this dissertation examined the influence of c-tDCS on motor skill acquisition, motor learning, and transfer of motor learning in PD. Collectively, the findings provided no evidence that c-tDCS applied in either the short or the long-term is an effective intervention to improve motor function in PD

Swayed by sound: sonic guidance as a neurorehabilitation strategy in the cerebellar ataxias

Cerebellar disease leads to problems in controlling movement. The most common difficulties are dysmetria and instability when standing. Recent understanding of cerebellar function has expanded to include non -motor aspects such as emotional, cognitive and sensory processing. Deficits in the acquisition and processing of sensory information are one explanation for the movement problems observed in cerebellar ataxia. Sensory deficits result in an inability to make predictions about future events; a primary function of the cerebellum. A question therefore, is whether augmenting or replacing sensory information can improve motor performance in cerebellar disease. This question is tested in this thesis by augmenting sensory information through the provision of an auditory movement guide.A variable described in motor control theory (tau) was used to develop auditory guides that were continuous and dynamic. A reaching experiment using healthy individuals showed that the timing of peak velocity, audiomotor coordination accuracy, and velocity of approach, could be altered in line with the movement parameters embedded in the auditory guides. The thesis then investigated the use of these sonic guides in a clinical population with cerebellar disease. Performance on neurorehabilitation exercises for balance control was tested in twenty people with cerebellar atrophy, with and without auditory guides. Results suggested that continuous, predictive, dynamic auditory guidance is an effective way of improving iii movement smoothness in ataxia (as measured by jerk). In addition, generating and swaying with imaginary auditory guides was also found to increase movement smoothness in cerebellar disease.Following the tests of instantaneous effects, the thesis then investigated the longterm consequences on motor behaviour of following a two -month exercise with auditory guide programme. Seven people with cerebellar atrophy were assessed pre - and post -intervention using two measures, weight -shifting and walking. The results of the weight -shifting test indicated that the sonic -guide exercise programme does not initiate long -term changes in motor behaviour. Whilst there were minor, improvements in walking, because of the weight -shifting results, these could not be attributed to the sonic guides. This finding confirms the difficulties of motor rehabilitation in people with cerebellar disease.This thesis contributes original findings to the field of neurorehabilitation by first showing that on -going and predictive stimuli are an appropriate tool for improving motor behaviour. In addition, the thesis is the first of its kind to apply externally presented guides that convey continuous meaningful information within a clinical population. Finally, findings show that sensory augmentation using the auditory domain is an effective way of improving motor coordination in some forms of cerebellar disease