Quantifying the Effects of Systematic STN-DBS Programming on Rest and Postural Tremor in Idiopathic Parkinson Disease Patients

Parkinson’s disease (PD) is a complex neurodegenerative disorder that encompasses both motor and non-motor symptoms. These symptoms and their severity are typically assessed by scale based measures in a clinical setting. Scale- based assessments of PD patients undergoing bilateral subthalamic nucleus deep brain stimulation surgery (STN-DBS) such as the Unified Parkinson Disease Rating Scale (UPDRS) are commonly used in a clinical setting to assess symptom severity and progression. However, the subjective nature of these and other clinical scales call into question both the sensitivity and accuracy of patient assessment over time. An objective quantification of rest and postural tremor of PD patients who have undergone STN-DBS has never been conducted. Furthermore, objective technologies that quantitatively assess the effects of STN-DBS programming on full body rest and postural tremor have not yet been fully explored. The study employed the use of a full body kinematic Inertial Motion Unit (IMU) based technology in order to study the short term and long term effects of Deep Brain Stimulation (DBS) on idiopathic PD patients. Not surprisingly both whole body rest and upper postural tremor reduced by six months following DBS surgery. An average best setting was identified for tremor reduction

Free-living monitoring of Parkinson’s disease: lessons from the field

Wearable technology comprises miniaturized sensors (e.g. accelerometers) worn on the body and/or paired with mobile devices (e.g. smart phones) allowing continuous patient monitoring in unsupervised, habitual environments (termed free-living). Wearable technologies are revolutionising approaches to healthcare due to their utility, accessibility and affordability. They are positioned to transform Parkinson’s disease (PD) management through provision of individualised, comprehensive, and representative data. This is particularly relevant in PD where symptoms are often triggered by task and free-living environmental challenges that cannot be replicated with sufficient veracity elsewhere. This review concerns use of wearable technology in free-living environments for people with PD. It outlines the potential advantages of wearable technologies and evidence for these to accurately detect and measure clinically relevant features including motor symptoms, falls risk, freezing of gait, gait, functional mobility and physical activity. Technological limitations and challenges are highlighted and advances concerning broader aspects are discussed. Recommendations to overcome key challenges are made. To date there is no fully validated system to monitor clinical features or activities in free living environments. Robust accuracy and validity metrics for some features have been reported, and wearable technology may be used in these cases with a degree of confidence. Utility and acceptability appears reasonable, although testing has largely been informal. Key recommendations include adopting a multi-disciplinary approach for standardising definitions, protocols and outcomes. Robust validation of developed algorithms and sensor-based metrics is required along with testing of utility. These advances are required before widespread clinical adoption of wearable technology can be realise

Inertial sensor based full body 3D kinematics in the differential diagnosis between Parkinson’s Disease and mimics

The differential diagnosis of Parkinson’s Disease (PD) remains challenging with frequent mis and underdiagnosis. DAT-Scan has been a useful technique for assessing the lost integrity of the nigrostriatal pathway in PD and differentiating true parkinsonism from mimics. However, DAT-Scan remains unavailable in most non-specialized clinical centres, making imperative the search for other easy and low-cost solutions. This dissertation aimed to investigate the role of inertial sensors in distinguishing between the denervated and the non-denervated individuals. In this dissertation, we've used Inertial Sensor Based 3D Full Body Kinematics (FBK) and tested if this technique was able to distinguish between patients with changes in the DAT-Scan from those without. This was divided into two parts, being that firstly, a group of individuals was referred by the attending physician for DAT-Scan (123I-FP-CIT SPECT) to be able to compare FBK in those with and without evidence of dopaminergic depletion. Second, it was tested whether FBK could be used as a metric for the severity of dopaminergic depletion. Twenty-one patients participated in this study, being recruited from the Nuclear Medicine Unit in the Champalimaud Clinical Centre (CCC), Lisbon. Within these 21 patients, 10 of them had denervation (mean age, 68.4 ± 7.8 years) and the remaining 11 (mean age, 66.6 ± 7.4 years) did not present denervation. The analysis between the worst uptake ratio features and dimensional features, as well as the asymmetry indexes in the striatum revealed significant differences between denervated and non-denervated individuals. On the contrary, the kinematics did not do it. Overall, based on the collected kinematics data, it was identified that there was not any significant correlation between the kinematics and the DAT-Scan. What means that these kinematics variables were not able to explain the DAT-Scan. On the other hand, it was also checked that the kinematics data were strongly correlated to the motor symptoms (MDS-UPDRS III). This way, it was concluded that the classical biomechanics did not distinguish denervated from non-denervated individuals. Therefore, the kinematics could not give the same answer as the DAT-Scan. In spite of these results it would be relevant to keep researching other methods in order to find out the distinction between the denervation and no denervation in a low-cost way

Wearable inertial sensors for human movement analysis

Introduction: The present review aims to provide an overview of the most common uses of wearable inertial sensors in the field of clinical human movement analysis.Areas covered: Six main areas of application are analysed: gait analysis, stabilometry, instrumented clinical tests, upper body mobility assessment, daily-life activity monitoring and tremor assessment. Each area is analyzed both from a methodological and applicative point of view. The focus on the methodological approaches is meant to provide an idea of the computational complexity behind a variable/parameter/index of interest so that the reader is aware of the reliability of the approach. The focus on the application is meant to provide a practical guide for advising clinicians on how inertial sensors can help them in their clinical practice.Expert commentary: Less expensive and more easy to use than other systems used in human movement analysis, wearable sensors have evolved to the point that they can be considered ready for being part of routine clinical routine

Senzorski sistem za objektivnu motornu procenu na osnovu tapping-a prstima i stopalom

Background/Aim. Finger tapping test is commonly used in neurological examinations as a test of motor performance. The new system comprising inertial and force sensors and custom proprietary software was developed for quantitative estimation and assessment of finger and foot tapping tests. The aim of this system was to provide diagnosis support and objective assessment of motor function. Methods. Miniature inertial sensors were placed on fingertips and used for measuring finger movements. A force sensor was placed on the fingertip of one finger, in order to measure the force during tapping. For foot tapping assessment, an inertial sensor was mounted on the subject's foot, which was placed above a force platform. By using this system, various parameters such as a number of taps, tapping duration, rhythm, open and close speed, the applied force and tapping angle, can be extracted for detailed analysis of a patient's motor performance. The system was tested on 13 patients with Parkinson's disease and 14 healthy controls. Results. The system allowed easy measurement of listed parameters, and additional graphical representation showed quantitative differences in these parameters between neurological patient and healthy subjects. Conclusion. The novel system for finger and foot tapping test is compact, simple to use and efficiently collects patient data. Parameters measured in patients can be compared to those measured in healthy subjects, or among groups of patients, or used to monitor progress of the disease, or therapy effects. Created data and scores could be used together with the scores from clinical tests, providing the possibility for better insight into the diagnosis.Uvod/Cilj. Tapping tj. tapkanje prstiju šake i stopala se uobičajeno koristi u neurološkim ispitivanjima kao test motorike. Prikazan je novi sistem koji sadrži inercijalne senzore i senzore sile, kao i odgovarajući softver za kvantitativnu procenu dijagnostičkog motornog testa na osnovu tapping-a prstima i stopalima. Uz pomoć ovog sistema moguća je objektivna evaluacija motornog obrasca bolesnika, a samim tim i lakše postavljanje određenih dijagnoza i praćenje progresa bolesti ili terapije. Metode. Minijaturni inercijalni senzori su bili postavljeni na vrhove prstiju u cilju kvantifikovanja pokreta prstiju. Senzor sile postavljen je na jagodicu jednog prsta i merio je silu primenjenu u toku tapping-a - tapkanja kažiprsta o palac. Za ocenu tapping-a stopalom, inercijalni senzor je postavljen na gornji deo stopala ispitanika koje je bilo postavljeno na platformu za merenje sile. Pomoću ovog sistema mogu se posmatrati brojni parametri poput broja i trajanja svakog pokreta, ritma i promena ritma, brzine otvaranja i brzine zatvaranja prstiju, primenjene sile, promene ugla između prstiju, i na osnovu ovih parametara može se vršiti detaljna analiza motornog stanja bolesnika. Sistem je testiran na 13 bolesnika sa Parkinsonovom bolešću i 14 zdravih ispitanika. Rezultati. Sistem je omogućio jednostavno merenje navedenih parametara i grafički prikaz kvantitativnih razlika u ovim parametrima između zdravih ispitanika i bolesnika sa neurološkim oboljenjem. Zaključak. Novi sistem za tapping prstima i stopalima je kompaktan, jednostavan za upotrebu i efikasan za prikupljanje podataka o bolesniku. Izmereni parametri mogu se koristi za poređenje bolesnika sa zdravim ispitanicima, ili sa drugim grupama bolesnika, ali i za praćenje progresa bolesti ili efekata terapije. Dobijeni podaci mogu se koristiti zajedno sa rezultatima drugih kliničkih testova, dajući tako mogućnost za bolji uvid u dijagnozu

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

Wearable health monitor to aid Parkinson's disease treatment

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003.Includes bibliographical references (leaf 31).by Joshua A. Weaver.S.M