Quantitative Messung vom Gehen auf der Stelle zur Erhebung von motorischen Symptomen bei Morbus Parkinson

Fluctuating motor symptoms are one of the main challenges in the assessment and evaluation of treatment effects in Parkinson’s disease (PD). The stepping in place task was previously proposed as an assessment of postural control and as surrogate for gait tests, two important evaluations of disturbed motor functions in this disorder. Due to its low spatial requirement, this motor task might specifically be suitable for an instrumental assessment even in remote application. Objective of this study was to explore the quantification of motor features associated with Parkinson's Diseases during stepping in place performance. Methods: Performance of 40 sec stepping in place (SIP) was recorded with a marker-free motion analysis system using a single RGB-Depth camera system. Data from 25 Persons with PD (PwPD, 7 female, Age: mean 65.3 years ± 9.4 years, MDS-UPDRS III 5-65) in up to two different treatment states (OFF: 13, ON: 20) and data from 83 healthy controls (HC, 52 female, Age: 36.8y ± 13.8y) was available for algorithm development, feature extraction and statistical analysis. Based on knee movements, eight spatiotemporal parameters were extracted including cadence, average knee movement amplitude, average and longest step and stance times, asymmetry and arrhythmicity. Parameters were analysed regarding potential confounding effects, technical accuracy and repeatability in HC, their relation to disease severity (MDS-UPDRS III) and postural instability (pull test score) in PwPD and intra- individual differences in treatment states (OFF vs. ON). Results: Six out of eight features showed good accuracy and repeatability in HC subgroup (n=19). Asymmetry and arrhythmicity showed only poor to moderate accuracy (ICC(A,1) > .3; Pearson’s r > .5) and repeatability (ICC(1,1) >.4). No linear confounding effects of age, height and weight were found in HC and PwPD. Decreased knee amplitude was associated with higher disease severity (rho = -.503, p-value = .003) and higher postural instability (rho = - .436, p-value = .014). Knee amplitudes showed also increase of 85.4% from OFF to ON in a subgroup in which recordings were available from both treatment states (n=10). Longer stance time measures were associated with higher disease severity (rho = .523, p-value = .002) and higher postural instability (rho = .468, p-value = .008). 50% of patients with ratings of freezing of gait during MDS-UPDRS III assessment showed freezing during SIP. Conclusion: Instrumental assessment of a 40 sec stepping in place performance may be suitable to quantify common motor symptoms, specifically postural instability, in PwPD. Derived parameters described motor symptoms of PD including decreased ranges of motion (hypokinesia), slower motions (bradykinesia) and increased asymmetry as well as arrhythmicity of stepping movements during SIP. Sensitivity to intra-individual changes, indicates potential use of SIP to monitor fluctuation of motor symptoms in PD.Motorische Fluktuationen sind eine der größten Herausforderungen bei der Beurteilung von Behandlungseffekten bei Morbus Parkinson (PD). Das auf der Stelle Gehen (SIP), wurde ursprünglich als Test zur Haltungskontrolle und als Surrogat für Ganganalyse vorgeschlagen, zwei wichtige Aspekte der gestörten motorischen Funktionen bei Parkinson. Ziel dieser Studie war es, die Quantifizierung von Parkinson-assoziierten motorischen Merkmalen während des Gehens auf der Stelle zu untersuchen. Methoden: Ein makerfreies Bewegungsanalysesystem (RGB-Tiefenkamera) wurde verwendet, um die Ausführung vom SIP über 40 Sekunden aufzuzeichnen. Für die Entwicklung der Algorithmen, die Merkmalsextraktion und die statistische Analyse standen Daten von 25 Personen mit Morbus Parkinson (PwPD, 7 weiblich, Alter: 65,3 Jahre ± 9,4 Jahre, MDS-UPDRS III 5-65) in bis zu zwei verschiedenen Therapiezuständen (OFF: 13, ON: 20) und Daten von 83 gesunden Personen (HC, 52 weiblich, Alter: 36,8 Jahre ± 13,8 Jahre) zur Verfügung. Auf Grundlage der Kniebewegungen wurden acht Parameter extrahiert: Kadenz, durchschnittliche Amplitude der Kniebewegung, durchschnittliche und längste Schritt- und Standzeiten, Asymmetrie und Arrhythmie. Die Parameter wurden im Hinblick auf potenzielle Störfaktoren, technische Genauigkeit und Wiederholbarkeit bei HC, Zusammenhang mit dem Schweregrad der Erkrankung (MDS-UPDRS III) und der posturalen Instabilität (Pull-Test-Score) in PwPD sowie auf intraindividuelle Unterschiede bei den Behandlungszuständen (OFF vs. ON) analysiert. Ergebnisse: Sechs von acht Merkmalen zeigten eine gute Genauigkeit und Wiederholbarkeit in HC (n=19). Asymmetrie und Arrhythmie zeigten nur geringe bis mäßige Genauigkeit (ICC(A,1) > .3; Pearson's r > .5) und Wiederholbarkeit (ICC(1,1) >.4). Bei HC (n=83) und PwPD (n=33) wurden keine linearen Effekte von Alter, Größe und Gewicht festgestellt. Eine verringerte Knieamplitude war mit höherer Krankheitsschwere (rho=-.503, p-Wert = .003) und höherer posturalen Instabilität (rho=-.436, p-Wert=.014) verbunden. Die Knieamplituden nahmen in einer Untergruppe (n=10), von OFF zu ON um 85,4 % zu. Längere Standzeiten waren mit höherer Krankheitsschwere (rho=.523, p-Wert=.002) und höherer posturalen Instabilität (rho=.468, p-Wert=.008) verbunden. 50 % der Patienten, die im MDS-UPDRS-III ein Einfrieren des Gangs zeigten, zeigten auch beim SIP ein Einfrieren. Schlussfolgerung: Die instrumentelle Analyse vom 40-sekündigen Gehen auf der Stelle kann geeignet sein, häufige motorische Symptome, insbesondere posturale Instabilität, bei PwPD zu quantifizieren. Die abgeleiteten Parameter beschrieben die motorischen Symptome von Morbus Parkinson, einschließlich verringerten Bewegungsumfang (Hypokinese), langsamerer Bewegungen (Bradykinese) und Asymmetrie sowie Arrhythmie der Schrittbewegungen. Die Empfindlichkeit gegenüber intraindividuellen Veränderungen deutet auf einen möglichen Einsatz des SIP zum Monitoring motorischer Symptome von PD hin

Implementation of a Computer-Vision System as a Supportive Diagnostic Tool for Parkinson’s Disease

Parkinson’s disease is the second most common neurodegenerative disorder, affecting nearly 1 million people in the US and it is predicted that the number will keep increasing. Parkinson’s disease is difficult to diagnose due to its similarity with other diseases that share the parkinsonian symptoms and the subjectivity of its assessment, thus increasing the probabilities of misdiagnosis. Therefore, it is relevant to develop diagnostic tools that are quantitatively based and monitoring tools to improve the patient’s quality of life. Computer-based assessment systems have shown to be successful in this field through diverse approaches that can be classified into two main categories: sensor-based and computer vision-based systems. In this thesis, the implementation of a computer vision system to detect Parkinson’s disease is explored. As Parkinson’s diseases has characteristic motor symptoms, and gait is mainly affected, a computer vision system is proposed to analyze the gait features to classify subjects with Parkinson’s disease. Using Microsoft’s Kinect sensor and Azure Kinect sensor, the position of body joints in a 3D space was obtained and angles between those were calculated. The standard deviation of 7 different angles over time was calculated for each and used as features in a support vector machine with the purpose of classifying Parkinson’s disease patients versus controls. Moreover, challenges and future perspectives for the implementation of computer-vision systems as supportive diagnostic tools for Parkinson’s disease are discussed

Kinect-based Solution for the Home Monitoring of Gait and Balance in Elderly People with and without Neurological Diseases

Alterations of gait and balance are a significant cause of falls, injuries, and consequent hospitalizations in the elderly. In addition to age-associated motor decline, other factors can impact gait and stability, including the motor dysfunctions caused by neurological diseases such as Parkinson’s disease or hemiplegia after stroke. Monitoring changes and deterioration in gait patterns and balance is crucial for activating rehabilitation treatments and preventing serious consequences. This work presents a Kinect-based solution, suitable for domestic contexts, for assessing gait and balance in individuals at risk of falling. The system captures body movements during home acquisition sessions scheduled by clinicians at definite times of the day and automatically estimates specific functional parameters to objectively characterize the subjects’ performance. The system includes a graphical user interface designed to ensure usability in unsupervised contexts: the human-computer interaction mainly relies on natural body movements to support the self-management of the system, if the motor conditions allow it. This work presents the system’s features and facilities, and the preliminary results on healthy volunteers’ trials

Sistema para análise automatizada de movimento durante a marcha usando uma câmara RGB-D

Nowadays it is still common in clinical practice to assess the gait (or way of walking) of a given subject through the visual observation and use of a rating scale, which is a subjective approach. However, sensors including RGB-D cameras, such as the Microsoft Kinect, can be used to obtain quantitative information that allows performing gait analysis in a more objective way. The quantitative gait analysis results can be very useful for example to support the clinical assessment of patients with diseases that can affect their gait, such as Parkinson’s disease. The main motivation of this thesis was thus to provide support to gait assessment, by allowing to carry out quantitative gait analysis in an automated way. This objective was achieved by using 3-D data, provided by a single RGB-D camera, to automatically select the data corresponding to walking and then detect the gait cycles performed by the subject while walking. For each detected gait cycle, we obtain several gait parameters, which are used together with anthropometric measures to automatically identify the subject being assessed. The automated gait data selection relies on machine learning techniques to recognize three different activities (walking, standing, and marching), as well as two different positions of the subject in relation to the camera (facing the camera and facing away from it). For gait cycle detection, we developed an algorithm that estimates the instants corresponding to given gait events. The subject identification based on gait is enabled by a solution that was also developed by relying on machine learning. The developed solutions were integrated into a system for automated gait analysis, which we found to be a viable alternative to gold standard systems for obtaining several spatiotemporal and some kinematic gait parameters. Furthermore, the system is suitable for use in clinical environments, as well as ambulatory scenarios, since it relies on a single markerless RGB-D camera that is less expensive, more portable, less intrusive and easier to set up, when compared with the gold standard systems (multiple cameras and several markers attached to the subject’s body).Atualmente ainda é comum na prática clínica avaliar a marcha (ou o modo de andar) de uma certa pessoa através da observação visual e utilização de uma escala de classificação, o que é uma abordagem subjetiva. No entanto, existem sensores incluindo câmaras RGB-D, como a Microsoft Kinect, que podem ser usados para obter informação quantitativa que permite realizar a análise da marcha de um modo mais objetivo. Os resultados quantitativos da análise da marcha podem ser muito úteis, por exemplo, para apoiar a avaliação clínica de pessoas com doenças que podem afetar a sua marcha, como a doença de Parkinson. Assim, a principal motivação desta tese foi fornecer apoio à avaliação da marcha, permitindo realizar a análise quantitativa da marcha de forma automatizada. Este objetivo foi atingido usando dados em 3-D, fornecidos por uma única câmara RGB-D, para automaticamente selecionar os dados correspondentes a andar e, em seguida, detetar os ciclos de marcha executados pelo sujeito durante a marcha. Para cada ciclo de marcha identificado, obtemos vários parâmetros de marcha, que são usados em conjunto com medidas antropométricas para identificar automaticamente o sujeito que está a ser avaliado. A seleção automatizada de dados de marcha usa técnicas de aprendizagem máquina para reconhecer três atividades diferentes (andar, estar parado em pé e marchar), bem como duas posições diferentes do sujeito em relação à câmara (de frente para a câmara e de costas para ela). Para a deteção dos ciclos da marcha, desenvolvemos um algoritmo que estima os instantes correspondentes a determinados eventos da marcha. A identificação do sujeito com base na sua marcha é realizada usando uma solução que também foi desenvolvida com base em aprendizagem máquina. As soluções desenvolvidas foram integradas num sistema de análise automatizada de marcha, que demonstrámos ser uma alternativa viável a sistemas padrão de referência para obter vários parâmetros de marcha espácio-temporais e alguns parâmetros angulares. Além disso, o sistema é adequado para uso em ambientes clínicos, bem como em cenários ambulatórios, pois depende de apenas de uma câmara RGB-D que não usa marcadores e é menos dispendiosa, mais portátil, menos intrusiva e mais fácil de configurar, quando comparada com os sistemas padrão de referência (múltiplas câmaras e vários marcadores colocados no corpo do sujeito).Programa Doutoral em Informátic

An Internet- and Kinect-Based Multiple Sclerosis Fitness Intervention Training With Pilates Exercises: Development and Usability Study

background: balance impairments are common in people with multiple sclerosis (MS), with reduced ability to maintain position and delayed responses to postural adjustments. Pilates is a popular alternative method for balance training that may reduce the rapid worsening of symptoms and the increased risk of secondary conditions (eg, depression) that are frequently associated with physical inactivity.objective: In this paper, we aimed to describe the design, development, and usability testing of MS Fitness Intervention Training (MS-FIT), a Kinect-based tool implementing Pilates exercises customized for MS. methods: MS-FIT has been developed using a user-centered design approach (design, prototype, user feedback, and analysis) to gain the target user's perspective. a team composed of 1 physical therapist, 2 game programmers, and 1 game designer developed the first version of MS-FIT that integrated the knowledge and experience of the team with MS literature findings related to pilates exercises and balance interventions based on exergames. MS-FIT, developed by using the Unity 3D (Unity Technologies) game engine software with kinect Sensor V2 for Windows, implements exercises for breathing, posture, and balance. Feedback from an Italian panel of experts in MS rehabilitation (neurologists, physiatrists, physical therapists, 1 statistician, and 1 bioengineer) and people with MS was collected to customize the tool for use in MS. The context of MS-FIT is traveling around the world to visit some of the most important cities to learn the aspects of their culture through pictures and stories. At each stay of the travel, the avatar of a Pilates teacher shows the user the exercises to be performed. Overall, 9 people with MS (n=4, 44% women; mean age 42.89, SD 11.97 years; mean disease duration 10.19, SD 9.18 years; Expanded Disability Status Scale score 3.17, SD 0.75) were involved in 3 outpatient user test sessions of 30 minutes; MS-FIT's usability was assessed through an ad hoc questionnaire (maximum value=5; higher the score, higher the usability) evaluating easiness to use, playability, enjoyment, satisfaction, and acceptance.Results: A user-centered design approach was used to develop an accessible and challenging tool for balance training. all people with MS (9/9, 100%) completed the user test sessions and answered the ad hoc questionnaire. the average score on each item ranged from 3.78 (SD 0.67) to 4.33 (SD 1.00), which indicated a high usability level. The feedback and suggestions provided by 64% (9/14) of people with MS and 36% (5/14) of therapists involved in the user test were implemented to refine the first prototype to release MS-FIT 2.0. Conclusions: The participants reported that MS-FIT was a usable tool. It is a promising system for enhancing the motivation and engagement of people with MS in performing exercise with the aim of improving their physical status

Recent advances in rehabilitation for Parkinson’s Disease with Exergames: A Systematic Review

Objective: The goal of this contribution is to gather and to critically analyze recent evidence regarding the potential of exergaming for Parkinson’s disease (PD) rehabilitation and to provide an up-to-date analysis of the current state of studies on exergame-based therapy in PD patients. Methods: We performed our search based on the conclusions of a previous systematic review published in 2014. Inclusion criteria were articles published in the indexed databases Pubmed, Scopus, Sciencedirect, IEEE and Cochrane published since January 1, 2014. Exclusion criteria were papers with a target group other than PD patients exclusively, or contributions not based on exergames. Sixty-four publications out of 525 matches were selected. Results: The analysis of the 64 selected publications confirmed the putative improvement in motor skills suggested by the results of the previous review. The reliability and safety of both Microsoft Kinect and Wii Balance Board in the proposed scenarios was further confirmed by several recent studies. Clinical trials present better (n = 5) or similar (n = 3) results than control groups (traditional rehabilitation or regular exercise) in motor (TUG, BBS) and cognitive (attention, alertness, working memory, executive function), thus emphasizing the potential of exergames in PD. Pilot studies (n = 11) stated the safety and feasibility of both Microsoft Kinect and Wii Balance Board, potentially in home scenarios as well. Technical papers (n = 30) stated the reliability of balance and gait data captured by both devices. Related metaanalyses and systematic reviews (n = 15) further support these statements, generally citing the need for adaptation to patient’s skills and new input devices and sensors as identified gaps. Conclusion: Recent evidence indicates exergame-based therapy has been widely proven to be feasible, safe, and at least as effective as traditional PD rehabilitation. Further insight into new sensors, best practices and different cognitive stadiums of PD (such as PD with Mild Cognitive Impairment), as well as task specificity, are required. Also, studies linking game parameters and results with traditional assessment methods, such as UPDRS scores, are required. Outcomes for randomized controlled trials (RCTs) should be standardized, and follow-up studies are required, particularly for motor outcomes

Phase Dynamics in Human Visuomotor Control - Health & Disease

In this thesis, comprised of four publications, I investigated phase dynamics of visuomotor control in humans during upright stance in response to an oscillatory visual drive. For this purpose, I applied different versions of a ‘moving room’ paradigm in virtual reality while stimulating human participants with anterior-posterior motion of their visual surround and analyzed their bodily responses. Human balance control constitutes a complex interplay of interdependent processes. The main sensory contributors include vision, vestibular input, and proprioception, with a dominant role attributed to vision. The purpose of the balance control system is to keep the body’s center of mass (COM) within a certain spatial range around the current base of support. Ever-changing environmental circumstances along with sensory noise cause the body to permanently sway around its point of equilibrium. Considering this sway, the human body can be modelled as a (multi-link) inverted pendulum. To maintain balance while being exposed to perturbations of the visual environment, humans adjust their sway to counteract the perceived motion of their bodies. Neurodegenerative diseases like Parkinson’s impair balance control and thus are likely to affect these mechanisms. Hence, investigation of bodily responses to a visual drive gives insight into visuomotor control in health and disease. In my first study, I introduced inter-trial phase coherence (ITPC) as a novel method to investigate postural responses to periodical visual stimulation. I found that human participants phase-locked the motion of their center of pressure (COP) to a 3-D dot cloud which oscillated in the anterior-posterior direction. This effect was equally strong for a low frequency of visual stimulation at 0.2 Hz and a high frequency of 1.5 Hz, the latter exceeding the previously assumed frequency range associated with coherent postural sway responses to periodical oscillations of the visual environment (moving room). Moreover, I was able to show that ITPC reliably captured responses in almost all participants, thereby addressing the common problem of inter-subject variability in body sway research. Based on the results of my first study, I concluded phase locking to be an essential feature in human postural control. For the second study, I introduced a mobile and cost-effective setup to apply a visual paradigm consisting of a virtual tunnel which stretched in the anterior-posterior direction and oscillated back and forth at three distinct frequencies (0.2 Hz, 0.8 Hz, and 1.2 Hz). Because tracking of the COP alone neglects crucial information about how COM shifts are arranged across the body, I included additional full-body motion tracking here to evaluate sway of individual body segments. Using a modified measure of phase locking, the phase locking value (PLV), allowed me to find participants phase-locking not only their COP, but also additional segments of their body to the visual drive. While their COP exhibited a strong phase locking to all frequencies of visual stimulation, distribution of phase locking across the body underwent a shift as the frequency of the visual stimulation increased. For the lowest frequency of 0.2 Hz, participants phase-locked almost their entire body to the stimulus. At higher frequencies, this phase locking shifted towards the lower torso and hip, with subjects almost exclusively phase-locking their hip to the visual drive at the highest frequency of 1.2 Hz. Having introduced a novel and reliable measurement along with a mobile setup, these results allowed me to empirically confirm shifts in postural strategies previously proposed in the literature. In the third study, a collaboration with the neurology department of the Universitätsklinikum Gießen und Marburg (UKGM), I used the same setup and paradigm as in the previous study and additionally derived the trajectory of the COM from a weighted combination of certain body segments. The aim was to investigate phase locking of body sway in a group of patients suffering from Parkinson’s disease (PD) to find potential means for an early diagnosis of the illness. For this purpose, I recruited a group of PD patients, an age-matched control group, and a group of young healthy adults. Even though the sway amplitude of PD patients was significantly larger than that of both other groups, they phase-locked their COP and COM in a similar manner as the control groups. However, considering individual body segments, the shift in PLV distribution differed between groups. While young healthy adults, analogous to the participants in the second study, exhibited a shift towards exclusive phase locking of their hips as frequency of the stimulation increased, both PD patients and age-matched controls maintained a rather homogeneous phase locking across their body. This suggested increased body stiffness, although being an effect of age rather than disease. Overall, I concluded that patients of early-to-mid stage PD exhibit impaired motor control, reflected in their increased sway amplitude, but intact visuomotor processing, indicated by their ability to phase-lock the motion of their body to a visual drive. The fourth study, to which I contributed as second author, used experimental data collected from an additional visual condition in the course of the third study. This condition consisted of unpredictable back and forward motion of the simulated tunnel. Here, we investigated the velocity profiles of the COP and COM in response to the unpredictable visual motion and a baseline condition at which the tunnel remained static. We found PD patients to exhibit larger velocities of their COP and COM under both conditions when compared to the control groups. When examining the net increase that unpredictable motion had on the velocity of both parameters, we found a significantly higher increase in COP velocity for both PD patients and age-matched controls, but no increase in COM velocity in any of the groups. These results suggested that all groups successfully maintained their balance under unpredictable visual perturbations, but that PD patients and older adults required more effort to accomplish this task, as reflected by the increased velocity of their COP. Again, these results indicated an effect of age rather than disease on the observed postural responses. In summary, using innovative phase-locking techniques and simultaneously tracking multiple body sway parameters, I was able to provide novel insight into visuomotor control in humans. First, I overcame previous issues of inconsistent sway parameters in groups of participants; Second, I found phase-locking to be an essential feature of visuomotor processing, which also allowed me to empirically confirm previously established theories of postural control; Third, through studies in collaboration with the neurology department of the UKGM, I was able to uncover new aspects of visuomotor processing in Parkinson’s, contributing to a better understanding of the sensorimotor aspects of the disease

Using 3D sensing and projecting technology to improve the mobility of Parkinson's disease patients

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonParkinson’s is a neurological condition in which parts of the brain responsible for movements becomes incapacitated over time due to the abnormal dopamine equilibrium. Freezing of Gait (FOG) is one of the main Parkinson’s Disease (PD) symptoms that affects patients not only physically but also psychologically as it prevents them from fulfilling simple tasks such as standing up or walking. Different auditory and visual cues have been proven to be very effective in improving the mobility of People with Parkinson’s (PwP). Nonetheless, many of the available methods require user intervention or devices to be worn, charged, etc. to activate the cues. This research suggests a system that can provide an unobtrusive facility to detect FOG and falling in PwP as well as monitoring and improving their mobility using laser-based visual cues casted by an automated laser system. It proposes a new indoor method for casting a set of two parallel laser lines as a dynamic visual cue in front of a subject’s feet based on the subject’s head direction and 3D location in a room. The proposed system controls the movement of a set of pan/tilt servo motors and laser pointers using a microcontroller based on the real-time skeletal information acquired from a Kinect v2 sensor. A Graphical User Interface (GUI) is created that enables users to control and adjust the settings based on the user preferences. The system was tested and trained by 12 healthy participants and reviewed by 15 PwP who suffer from frequent FOG episodes. The results showed the possibility of employing the system as an indoor and on-demand visual cue system for PwP that does not rely on the subject’s input or introduce any additional complexities to operate. Despite limitations regarding its outdoor use, feedback was very positive in terms of domestic usability and convenience, where 12/15 PwP showed interest in installing and using the system at their homes