Balance and gait in children with dyslexia

Tests of postural stability have provided some evidence of a link between deficits in gross motor skills and developmental dyslexia. The ordinal-level scales used previously, however, have limited measurement sensitivity, and no studies have investigated motor performance during walking in participants with dyslexia. The purpose of this study was to investigate if continuous-scaled measures of standing balance and gait could discriminate between groups of impaired and normal readers when investigators were blind to group membership during testing. Children with dyslexia (n=22) and controls (n=18), aged 10-12 years, performed walking tests at four different speeds (slow-preferred-fast-very fast) on an even and an uneven surface, and tests of unperturbed and perturbed body sway during standing. Body movements were registered by a triaxial accelerometer over the lower trunk, and measures of reaction time, body sway, walking speed, step length and cadence were calculated. Results were controlled for gender differences. Tests of standing balance with eyes closed did not discriminate between groups. All unperturbed standing tests with eyes open showed significant group differences (P<0.05) and classified correctly 70-77.5% of the subjects into their respective groups. Mean walking speed during very fast walking on both flat and uneven surface was ≥0.2 m/s (P≤0.01) faster for controls than for the group with dyslexia. This test classified 77.5% and 85% of the subjects correctly on flat and uneven surface, respectively Cadence at preferred or very fast speed did not differ statistically between groups, but revealed significant group differences when all subjects were compared at a normalised walking speed (P≤0.04). Very fast walking speed as well as cadence at a normalised speed discriminated better between groups when subjects were walking on an uneven surface compared to a flat floor. Continuous-scaled walking tests performed in field settings may be suitable for motor skill assessment as a component of a screening tool for developmental dyslexia.

The neurotoxicity of acrylamide

The experiments described in this thesis compared conventional methods of screening for neurotoxins with potential electrophysiological and pharmacological tests in an attempt to improve the sensitivity of detection of progressive distal neuropathy. Adult male albino mice were dosed orally with the neurotoxicant acylamide and subjected to a test of limb strength and co-ordination and a functional observational battery. These methods established a no observable effect level of 10 mg/kg. A dose of 200 mg/kg resulted in abnormalities of gait and reduced limb strength and/or co-ordination. Analysis of the in vitro 'jitter' of the latency of trains of action potentials evoked at a frequency of 30 Hz in the mouse phrenic nerve/hemidiaphragm preparation showed this technique to be unsuitable for detection of the early phases of acrylamide induced peripheral neuropathy (l00 mg/kg). The evoked and spontaneous twitch responses of the hemidiaphragm preparation following in vitro exposure to the organophosphorous anticholinesterase compound ecothiopate were altered by in vivo pre treatment with acrylamide. Acrylamide caused an increase in the time course of the potentiation of stimulated twitches and a decrease in the maximum potentiation. Spontaneous twitches were reduced in amplitude and frequency. These effects occurred at an acrylamide dose level insufficient to cause clinical signs of neuropathy. Investigations into the mechanisms underlying these observations yielded the following observations. Analysis of miniature endplate potentials at this dose level indicated prolongation of the life of acetylcholine in the synaptic cleft but the implied decrease in cholinesterase activity could not be demonstrated biochemically or histologically. The electrical excitability of the nerve terminal region of phrenic motor nerves was reduced following acrylamide although a possible compromise of antidromic action potential conduction could not be confirmed. There was no histopathological evidence of neuropathy at this dose level. Further exploration of this phenomenon is desirable in order to ascertain whether the effect is specific to acrylamide and/or ecothiopate and to elucidate the mechanisms behind these novel observations.

Visual signs and symptoms of progressive supranuclear palsy

Progressive supranuclear palsy is a rare, degenerative brain disorder and the second most common syndrome in which the patient exhibits 'parkinsonism', that is, a variety of symptoms involving problems with movement. General symptoms include difficulties with gait and balance; the patient walking clumsily and often falling backwards. The syndrome can be difficult to diagnose and visual signs and symptoms can help to separate it from closely related movement disorders such as Parkinson's disease, multiple system atrophy, dementia with Lewy bodies and corticobasal degeneration. A combination of the presence of vertical supranuclear gaze palsy, fixation instability, lid retraction, blepharospasm and apraxia of eyelid opening and closing may be useful visual signs in the identification of progressive supranuclear palsy. As primary eye-care practitioners, optometrists should be able to identify the visual problems of patients with this disorder and be expected to work with patients and their carers to manage their visual welfare.

A smart sensing platform for the discrimination of human movement

This thesis documents the design, implementation and testing of a smart sensing platform that is able to discriminate between differences or small changes in a persons walking. The distributive tactile sensing method is used to monitor the deflection of the platform surface using just a small number of sensors and, through the use of neural networks, infer the characteristics of the object in contact with the surface. The thesis first describes the development of a mathematical model which uses a novel method to track the position of a moving load as it passes over the smart sensing surface. Experimental methods are then described for using the platform to track the position of swinging pendulum in three dimensions. It is demonstrated that the method can be extended to that of real-time measurement of balance and sway of a person during quiet standing. Current classification methods are then investigated for use in the classification of different gait patterns, in particular to identify individuals by their unique gait pattern. Based on these observations, a novel algorithm is developed that is able to discriminate between abnormal and affected gait. This algorithm, using the distributive tactile sensing method, was found to have greater accuracy than other methods investigated and was designed to be able to cope with any type of gait variation. The system developed in this thesis has applications in the area of medical diagnostics, either as an initial screening tool for detecting walking disorders or to be able to automatically detect changes in gait over time. The system could also be used as a discrete biometric identification method, for example identifying office workers as they pass over the surface.

A smart sensing platform for the classification of ambulatory patterns

This paper describes an innovative sensing approach allowing capture, discrimination, and classification of transients automatically in gait. A walking platform is described, which offers an alternative design to that of standard force plates with advantages that include mechanical simplicity and less restriction on dimensions. The scope of the work is to investigate as an experiment the sensitivity of the distributive tactile sensing method with the potential to address flexibility on gait assessment, including patient targeting and the extension to a variety of ambulatory applications. Using infrared sensors to measure plate deflection, gait patterns are compared with stored templates using a pattern recognition algorithm. This information is input into a neural network to classify normal and affected walking events, with a classification accuracy of just under 90 per cent achieved. The system developed has potential applications in gait analysis and rehabilitation, whereby it can be used as a tool for early diagnosis of walking disorders or to determine changes between pre- and post-operative gait.

Footwear for gender recognition

Conventionally, biometrics resources, such as face, gait silhouette, footprint, and pressure, have been utilized in gender recognition systems. However, the acquisition and processing time of these biometrics data makes the analysis difficult. This letter demonstrates for the first time how effective the footwear appearance is for gender recognition as a biometrics resource. A footwear database is also established with reprehensive shoes (footwears). Preliminary experimental results suggest that footwear appearance is a promising resource for gender recognition. Moreover, it also has the potential to be used jointly with other developed biometrics resources to boost performance.

Distributive tactile sensing using fibre Bragg grating sensors for biomedical applications

Artificial tactile sensing systems using the distributive tactile sensing technique and fibre Bragg grating sensors are presented. A one-dimensional arrangement, with possible applications in an endoscope, is compared with a similar arrangement using conventional electronic sensors. A two-dimensional sensing surface is described, with potential applications in human balance and gait analysis, capable of detecting simultaneously the position and shape of an object placed upon it. It is believed that this work represents the first use of fibre Bragg grating sensors in a distributive sensing regime.

Corticobasal degeneration and dementia

Corticobasal degeneration is a rare, progressive neurodegenerative disorder which significantly impairs movement. The most common initial symptom is asymmetric limb clumsiness with or without accompanying rigidity or tremor. Subsequently, the disease progresses to affect gait and there is a slow progression to influence ipsilateral arms and legs. Apraxia and dementia are the most common cortical signs. Clinical diagnosis of the disorder is difficult as the symptoms resemble those of related neurodegenerative disorders. Histopathologically, there is widespread neuronal and glial pathology including tau-immunoreactive neuronal cytoplasmic inclusions, neuropil threads, oligodendroglial inclusions, astrocytic plaques, together with abnormally enlarged ‘ballooned’ neurons. Corticobasal degeneration has affinities both with the parkinsonian syndromes including Parkinson’s disease, progressive supranuclear palsy, and multiple system atrophy and with the fronto-temporal dementias. Treatment of corticobasal degeneration involves managing and reducing the effect of symptoms.

High accuracy discrimination of Parkinson's disease participants from healthy controls using smartphones

The aim of this study is to accurately distinguish Parkinson's disease (PD) participants from healthy controls using self-administered tests of gait and postural sway. Using consumer-grade smartphones with in-built accelerometers, we objectively measure and quantify key movement severity symptoms of Parkinson's disease. Specifically, we record tri-axial accelerations, and extract a range of different features based on the time and frequency-domain properties of the acceleration time series. The features quantify key characteristics of the acceleration time series, and enhance the underlying differences in the gait and postural sway accelerations between PD participants and controls. Using a random forest classifier, we demonstrate an average sensitivity of 98.5% and average specificity of 97.5% in discriminating PD participants from controls. © 2014 IEEE.

Detecting and monitoring the symptoms of Parkinson's disease using smartphones:a pilot study

Background: Remote, non-invasive and objective tests that can be used to support expert diagnosis for Parkinson's disease (PD) are lacking. Methods: Participants underwent baseline in-clinic assessments, including the Unified Parkinson's Disease Rating Scale (UPDRS), and were provided smartphones with an Android operating system that contained a smartphone application that assessed voice, posture, gait, finger tapping, and response time. Participants then took the smart phones home to perform the five tasks four times a day for a month. Once a week participants had a remote (telemedicine) visit with a Parkinson disease specialist in which a modified (excluding assessments of rigidity and balance) UPDRS performed. Using statistical analyses of the five tasks recorded using the smartphone from 10 individuals with PD and 10 controls, we sought to: (1) discriminate whether the participant had PD and (2) predict the modified motor portion of the UPDRS. Results: Twenty participants performed an average of 2.7 tests per day (68.9% adherence) for the study duration (average of 34.4 days) in a home and community setting. The analyses of the five tasks differed between those with Parkinson disease and those without. In discriminating participants with PD from controls, the mean sensitivity was 96.2% (SD 2%) and mean specificity was 96.9% (SD 1.9%). The mean error in predicting the modified motor component of the UPDRS (range 11-34) was 1.26 UPDRS points (SD 0.16). Conclusion: Measuring PD symptoms via a smartphone is feasible and has potential value as a diagnostic support tool.

High-accuracy discrimination of Parkinson’s Disease participants from healthy controls using smartphones

Objective: To test the practicality and effectiveness of cheap, ubiquitous, consumer-grade smartphones to discriminate Parkinson’s disease (PD) subjects from healthy controls, using self-administered tests of gait and postural sway. Background: Existing tests for the diagnosis of PD are based on subjective neurological examinations, performed in-clinic. Objective movement symptom severity data, collected using widely-accessible technologies such as smartphones, would enable the remote characterization of PD symptoms based on self-administered, behavioral tests. Smartphones, when backed up by interviews using web-based videoconferencing, could make it feasible for expert neurologists to perform diagnostic testing on large numbers of individuals at low cost. However, to date, the compliance rate of testing using smart-phones has not been assessed. Methods: We conducted a one-month controlled study with twenty participants, comprising 10 PD subjects and 10 controls. All participants were provided identical LG Optimus S smartphones, capable of recording tri-axial acceleration. Using these smartphones, patients conducted self-administered, short (less than 5 minute) controlled gait and postural sway tests. We analyzed a wide range of summary measures of gait and postural sway from the accelerometry data. Using statistical machine learning techniques, we identified discriminating patterns in the summary measures in order to distinguish PD subjects from controls. Results: Compliance was high all 20 participants performed an average of 3.1 tests per day for the duration of the study. Using this test data, we demonstrated cross-validated sensitivity of 98% and specificity of 98% in discriminating PD subjects from healthy controls. Conclusions: Using consumer-grade smartphone accelerometers, it is possible to distinguish PD from healthy controls with high accuracy. Since these smartphones are inexpensive (around $30 each) and easily available, and the tests are highly non-invasive and objective, we envisage that this kind of smartphone-based testing could radically increase the reach and effectiveness of experts in diagnosing PD.

Wearable sensors in Huntington disease:a pilot study

Background: The Unified Huntington’s Disease Rating Scale (UHDRS) is the principal means of assessing motor impairment in Huntington disease but is subjective and generally limited to in-clinic assessments. Objective: To evaluate the feasibility and ability of wearable sensors to measure motor impairment in individuals with Huntington disease in the clinic and at home. Methods: Participants with Huntington disease and controls were asked to wear five accelerometer-based sensors attached to the chest and each limb for standardized, in-clinic assessments and for one day at home. A secondchest sensor was worn for six additional days at home. Gait measures were compared between controls, participants with Huntington disease, and participants with Huntington disease grouped by UHDRS total motor score using Cohen’s d values. Results: Fifteen individuals with Huntington disease and five controls completed the study. Sensor data were successfully captured from 18 of the 20 participants at home. In the clinic, the standard deviation of step time (timebetween consecutive steps) was increased in Huntington disease (p<0.0001; Cohen’s d=2.61) compared to controls. At home with additional observations, significant differences were observed in seven additional gait measures. The gait of individuals with higher total motor scores (50 or more) differed significantly from those with lower total motor scores (below 50) on multiple measures at home. Conclusions: In this pilot study, the use of wearable sensors in clinic and at home was feasible and demonstrated gait differences between controls, participants with Huntington disease, and participants with Huntington diseasegrouped by motor impairment.

Mobility changes in older age: neuropsychological, neurophysiological and cognitive predictors of successful adaptation in a real world scenario

The aims of this thesis were to investigate the neuropsychological, neurophysiological, and cognitive contributors to mobility changes with increasing age. In a series of studies with adults aged 45-88 years, unsafe pedestrian behaviour and falls were investigated in relation to i) cognitive functions (including response time variability, executive function, and visual attention tests), ii) mobility assessments (including gait and balance and using motion capture cameras), iii) motor initiation and pedestrian road crossing behavior (using a simulated pedestrian road scene), iv) neuronal and functional brain changes (using a computer based crossing task with magnetoencephalography), and v) quality of life questionnaires (including fear of falling and restricted range of travel). Older adults are more likely to be fatally injured at the far-side of the road compared to the near-side of the road, however, the underlying mobility and cognitive processes related to lane-specific (i.e. near-side or far-side) pedestrian crossing errors in older adults is currently unknown. The first study explored cognitive, motor initiation, and mobility predictors of unsafe pedestrian crossing behaviours. The purpose of the first study (Chapter 2) was to determine whether collisions at the near-side and far-side would be differentially predicted by mobility indices (such as walking speed and postural sway), motor initiation, and cognitive function (including spatial planning, visual attention, and within participant variability) with increasing age. The results suggest that near-side unsafe pedestrian crossing errors are related to processing speed, whereas far-side errors are related to spatial planning difficulties. Both near-side and far-side crossing errors were related to walking speed and motor initiation measures (specifically motor initiation variability). The salient mobility predictors of unsafe pedestrian crossings determined in the above study were examined in Chapter 3 in conjunction with the presence of a history of falls. The purpose of this study was to determine the extent to which walking speed (indicated as a salient predictor of unsafe crossings and start-up delay in Chapter 2), and previous falls can be predicted and explained by age-related changes in mobility and cognitive function changes (specifically within participant variability and spatial ability). 53.2% of walking speed variance was found to be predicted by self-rated mobility score, sit-to-stand time, motor initiation, and within participant variability. Although a significant model was not found to predict fall history variance, postural sway and attentional set shifting ability was found to be strongly related to the occurrence of falls within the last year. Next in Chapter 4, unsafe pedestrian crossing behaviour and pedestrian predictors (both mobility and cognitive measures) from Chapter 2 were explored in terms of increasing hemispheric laterality of attentional functions and inter-hemispheric oscillatory beta power changes associated with increasing age. Elevated beta (15-35 Hz) power in the motor cortex prior to movement, and reduced beta power post-movement has been linked to age-related changes in mobility. In addition, increasing recruitment of both hemispheres has been shown to occur and be beneficial to perform similarly to younger adults in cognitive tasks (Cabeza, Anderson, Locantore, & McIntosh, 2002). It has been hypothesised that changes in hemispheric neural beta power may explain the presence of more pedestrian errors at the farside of the road in older adults. The purpose of the study was to determine whether changes in age-related cortical oscillatory beta power and hemispheric laterality are linked to unsafe pedestrian behaviour in older adults. Results indicated that pedestrian errors at the near-side are linked to hemispheric bilateralisation, and neural overcompensation post-movement, 4 whereas far-side unsafe errors are linked to not employing neural compensation methods (hemispheric bilateralisation). Finally, in Chapter 5, fear of falling, life space mobility, and quality of life in old age were examined to determine their relationships with cognition, mobility (including fall history and pedestrian behaviour), and motor initiation. In addition to death and injury, mobility decline (such as pedestrian errors in Chapter 2, and falls in Chapter 3) and cognition can negatively affect quality of life and result in activity avoidance. Further, number of falls in Chapter 3 was not significantly linked to mobility and cognition alone, and may be further explained by a fear of falling. The objective of the above study (Study 2, Chapter 3) was to determine the role of mobility and cognition on fear of falling and life space mobility, and the impact on quality of life measures. Results indicated that missing safe pedestrian crossing gaps (potentially indicating crossing anxiety) and mobility decline were consistent predictors of fear of falling, reduced life space mobility, and quality of life variance. Social community (total number of close family and friends) was also linked to life space mobility and quality of life. Lower cognitive functions (particularly processing speed and reaction time) were found to predict variance in fear of falling and quality of life in old age. Overall, the findings indicated that mobility decline (particularly walking speed or walking difficulty), processing speed, and intra-individual variability in attention (including motor initiation variability) are salient predictors of participant safety (mainly pedestrian crossing errors) and wellbeing with increasing age. More research is required to produce a significant model to explain the number of falls.

Visual signs and symptoms of corticobasal degeneration

Corticobasal degeneration is a rare, progressive neurodegenerative disease and a member of the 'parkinsonian' group of disorders, which also includes Parkinson's disease, progressive supranuclear palsy, dementia with Lewy bodies and multiple system atrophy. The most common initial symptom is limb clumsiness, usually affecting one side of the body, with or without accompanying rigidity or tremor. Subsequently, the disease affects gait and there is a slow progression to influence ipsilateral arms and legs. Apraxia and dementia are the most common cortical signs. Corticobasal degeneration can be difficult to distinguish from other parkinsonian syndromes but if ocular signs and symptoms are present, they may aid clinical diagnosis. Typical ocular features include increased latency of saccadic eye movements ipsilateral to the side exhibiting apraxia, impaired smooth pursuit movements and visuo-spatial dysfunction, especially involving spatial rather than object-based tasks. Less typical features include reduction in saccadic velocity, vertical gaze palsy, visual hallucinations, sleep disturbance and an impaired electroretinogram. Aspects of primary vision such as visual acuity and colour vision are usually unaffected. Management of the condition to deal with problems of walking, movement, daily tasks and speech problems is an important aspect of the disease.

Discriminating ambulation using a smart sensing plate

The automated sensing scheme described in this paper has the potential to automatically capture, discriminate and classify transients in gait. The mechanical simplicity of the walking platform offers advantages over standard force plates. There is less restriction on dimensions offering the opportunity for multi-contact and multiple steps. This addresses the challenge of patient targeting and the evaluation of patients in a variety of ambulatory applications. In this work the sensitivity of the distributive tactile sensing method has been investigated experimentally. Using coupled time series data from a small number of sensors, gait patterns are compared with stored templates using a pattern recognition algorithm. By using a neural network these patterns were interpreted classifying normal and affected walking events with an accuracy of just under 90%. This system has potential in gait analysis and rehabilitation as a tool for early diagnosis in walking disorders, for determining response to therapy and for identifying changes between pre and post operative gait. Copyright © 2009 by ASME.