The study of postural and motor impairments in patients with motor problems can give very important information to know the level of functional limitations resulting to the pathology and its evolution overtime. Furthermore, it provides important elements to assessing the efficacy of rehabilitation for recovery of pathological impairments. It is therefore, important, for those patients able to make use of innovative techniques and advanced equipment that allow describing, quantifying and evaluating the movement. The clinical evaluation of the movement, especially of walking, it is realized in laboratories, where patients have to perform some motor tasks, which are detected by different type of sensors. There are, among these, optoelectronic systems, which allowed computerized, multifactorial and integrated analysis of spatio-temporal and kinematic parameters of the walking, along with the electromyoagraphic signals of the muscles under observation. Alongside the recognized and certified strumentations for gait analysis, in the last 10-15 years new, economic portable systems have been developed, which are configured as wearable inertial sensors. Parkinson’s disease (PD) is a neurodegenerative disorder that affects nerve cells in a part of the brain that controls muscle movement. Symptoms of Parkinson’s disease may include resting tremor, bradykinesia, rigidity, postural instability and freezing. Although not present in all patients, freezing is perhaps the most debilitating symptom of Parkinson’s disease as it may lead to falls, a decrease in quality of life and loss of independence. Freezing of Gait (FOG) is a paroxysmal phenomenon commonly seen as an advanced symptom in Parkinson’s disease. The FOG events are transient, generally lasting for a few seconds, tending to increase in frequency as the disease progresses. There are three different subtypes of FOG. The well-known clinical manifestation is that of a patient who suddenly becomes incapable to start walking or fails to continue to move forward (akinesia). The second subtypes of FOG is related to complete absence of movement, while the third subtypes of FOG consists of shuffling forward with very short steps. If gait and movement evaluation of the subjects with Parkinson's disease can be made in the Motion Analysis laboratories, as documented by several studies in the literature, there is a need to move towards a simpler evaluation , suited to the type of patient and the needs of the clinic. The quantitative gait analysis performed in a movement analysis laboratory present the advantages to be precise, accurate, repeatable and providing with reliable results. On the other hand, the gait itself can be altered by the restrictions due to the dimensions of the measurement system, especially in those patients in which the cognitive aspect greatly affects the motor pattern. Moreover, an analysis conducted in laboratory does not take into account subjects’ mobility throughout the day, week, month or longer term, and the dayby-day environment where they usually perform the gait. The main objective of this thesis is verify if it is possible to characterize the freezing episode in Parkinson’s diseases patients, using inertial sensors. First of all, the first step of the work was the accuracy rating of the inertial sensor (GSensor) compared to the gold standard (optoelectronic system); for this reason were recruited, at the Laboratory of Analysis of the movement of the Clinic San Raffaele, in Cassini, 14 patients with Parkinson’s diseases, 7 of these affected by freezing. The patients were subjected to walking trials acquired with the optoelectronic system and with the wearable inertial sensor. The variables analysis for the comparison focused on those identified by previous studies such as those designed to characterize the phenomenon of freezing and in particular spatio-temporal and gait regularity indices. Statical analysis helped to identify if the sensor is able, first, to accurately estimate the selected variables, and more if it is able to perceive the differences between the group with Parkinson’s diseases with freezing than the group of patients with Parkinson’s diseases but without freezing. Another aim of work is to define a forecasting model to estimate that could estimate a synthetic freezing index, based on the variables acquired through a wearable sensor. Doing this, were selected, according to specific inclusion criteria, 20 patients, all suffering from Parkinson's disease aggravated by freezing episodes. These patients had undergone to several walking trials, acquired with a wearable inertial devices, at the Laboratory of Movement Analysis of the Federal University of Health Sciences of Porto Alegre, in Brazil. Starting from the results obtained from the comparative study, have been selected the parameters to be entered into the forecasting model. Applying multiple linear regression analysis, the model was developed in order to obtain a synthetic index, which represents, with a unique number, the probability of occurrence of freezing, estimating the value of the FOG - Q scale. The last goal is to apply the identified index on the sample of 20 patients, who had undergone a rehabilitation treatment, based on Automated Mechanical Peripheral Stimulation (AMPS). In this context, the database has been divided into two subgroups of 10 subjects: while one group was treated with AMPS, the other has been treated with a placebo stimulation. A statistical analysis has determined if through this synthetic index it is possible to point out, during the AMPS treatment sessions, the statistically significant differences emerged from a previous study on the same patient database, carried out with measures using optoelectronic systems and tests of Gait Analysis . The data provided from the comparative study showed that although, G-Sensor is not able to produce results not always as much accurate and precise as those of a gold standard measurement system, it could be successfully be used in monitoring the general condition of a patient. Anyhow, all the advantages regarding as the cheap technology, the easy to implement procedure applicable in ambulatory contexts, non invasivity, ecology and possibility to get objective quantitative data without the expensive facilities of a movement analysis laboratory make G-sensor a very suitable choice in this field of clinical analysis. Finally, the results obtained with the synthetic index reflect the good results achieved from the Gait Analysis study. So this type of FOG index can be regarded as an acceptable method of evaluation that in a simple and immediate way allows giving an approximate indication regarding the freezing conditions of the subject in analysis.
Lo studio della alterazione posturale e motoria in pazienti con problemi motori può dare informazioni molto importanti per conoscere il livello di limitazione funzionale conseguente alla patologia e del suo evolversi nel tempo. Inoltre fornisce importanti elementi di valutazione dell’efficacia di interventi riabilitativi nel recupero delle alterazioni conseguenti allo stato patologico. Risulta quindi di fondamentale importanza, soprattutto per questi pazienti, potersi avvalere di tecniche innovative e strumentazioni all’avanguardia che permettano di descrivere, quantificare e valutare il movimento. La valutazione clinica del movimento, in particolare del cammino, è comunemente realizzata all’interno di laboratori in cui i pazienti sono chiamati a svolgere alcuni gesti motori che vengono rilevati tramite una strumentazione specifica. Tra questi si citano i sistemi optoelettronici, che permettono un’analisi computerizzata multifattoriale e integrata dei parametri spazio-temporali e cinematici del cammino, insieme ai segnali elettromiografici dei muscoli sotto osservazione. Accanto alle strutture riconosciute e certificate per l’analisi del cammino, negli ultimi 10-15 anni sono stati sviluppati nuovi sistemi portatili, a basso costo, che si configurano come sensori inerziali indossabili. La malattia di Parkinson, è una patologia neurodegenerativa che complisce le cellule nervose in una parte del cervello deputata al controllo del movimento. I sintomi della Malattia di Parkinson possono includere tremore a riposo, bradicinesia, rigidità, instabilità posturale e Freezing (Freezing Of Gait, FOG). Sebbene non presente in tutti i pazienti, il freezing è probabilmente il sintomo più debilitante della Malattia di Parkinson, infatti oltre ad essere la principale causa di cadute, porta ad una graduale perdita di indipendenza e alla riduzione della qualità della vita. Il FOG è un fenomeno prossimale che si manifesta con il progredire della malattia. Gli eventi di freezing sono transienti e generalmente durano qualche secondo, tendendo ad aumentare in frequenza con l’avanzamento della malattia. Esistono tre sottotipi di FOG. Quello più conosciuto consiste nell’incapacità del paziente di cominciare a camminare o nel fallimento del tentativo di proseguire nel movimento (acinesia). La seconda tipologia di FOG è correlata alla completa assenza di movimento, mentre il terzo sottotipo consiste in un’andatura festinante, determinata da passi brevi e frequenti. Se la valutazione della deambulazione e del movimento in generale del soggetto con malattia di Parkinson può essere fatta in laboratori di analisi del movimento, come documentato da diversi studi in letteratura, vi è la necessità di andare verso una valutazione più semplice, adatta al tipo di paziente e alle esigenze della clinica. L’analisi quantitativa del cammino, effettuata in un laboratorio di analisi del movimento, presenta vantaggi in termini di precisione, accuratezza e ripetibilità del dato, fornendo dei risultati affidabili. D’altra parte, il cammino può essere alterato dalle restrizioni dovute alle dimensioni del sistema di misura, specialmente in quei pazienti in cui l’aspetto cognitivo incide notevolmente sul pattern motorio. Inoltre, un’analisi condotta in laboratorio non può tener conto della mobilità dei pazienti durante il giorno, la settimana, il mese o a lungo termine, e dell’ambiente, in cui giorno per giorno, questi pazienti camminano. Il principale obbiettivo di questa tesi è verificare se sia possibile caratterizzare il fenomeno del freezing in soggetti con Malattia di Parkinson, attraverso l’utilizzo di sensori inerziali. Inizialmente, il primo step del lavoro ha visto la valutazione dell’accuratezza del sensore inerziale a nostra disposizione (G-Sensor) rispetto al Gold standard (sistema optoelettronico); a tal fine sono stati reclutati, presso il Laboratorio di Analisi del movimento della Casa di Cura San Raffaele di Cassino, 14 pazienti affetti da Malattia di Parkinson, di cui 7 con freezing. I pazienti sono stati sottoposti a prove di cammino acquisite sia con il sistema optoelottronico che con il sensore inerziale indossabile. L’analisi delle variabili per il confronto si è concentrata su quelle identificate dagli studi precedenti come quelle atte a caratterizzare il fenomeno del freezing ed in particolare indici spazio temporali e di regolarità del passo. Un’analisi statistica ha consentito di individuare se il sensore sia in grado, in primis, di stimare accuratamente le variabili selezionate, e in più se sia capace di percepire le differenze tra il gruppo con Malattia di Parkinson con freezing rispetto al gruppo di pazienti con Malattia di Parkinson ma senza freezing. Un ulteriore obbiettivo del lavoro è quello di definire un modello di previsione in grado di stimare un indice sintetico di freezing, basato sulle variabili acquisite mediante un sensore indossabile. Per fare ciò, sono stati selezionati, secondo particolari criteri di inclusione, 20 pazienti, tutti affetti da Malattia di Parkinson aggravata da episodi di freezing. Questi pazienti sono stati sottoposti a prove di cammino presso il laboratorio di Analisi del Movimento dell’Università Federale delle Scienze della Salute di Porto Alegre, in Brasile, acquisite con il sensore inerziale. A partire dai risultati ottenuti dallo studio comparativo, sono stati selezionati i parametri da inserire nel modello di previsione. Applicando un’analisi di regressione lineare multipla, tale modello è stato sviluppato in modo da ottenere un indice sintetico che rappresenti, con un unico numero, la probabilità di insorgenza di freezing nel paziente, stimando il valore della scala FOG-Q. L’ultimo obbiettivo consiste nell’applicare l’indice identificato sul campione di 20 pazienti, i quali sono stati sottoposti ad un trattamento riabilitativo, di 8 sessioni, basato sulla Stimolazione Meccanica Automatizzata Periferica (AMPS). In questo contesto, il database di pazienti è stato suddiviso in due gruppi di 10 soggetti ciascuno: mentre un gruppo è stato trattato con AMPS, l’altro è stato sottoposto ad un trattamento placebo. Un’analisi statistica ha stabilito se tramite questo indice sintetico possano essere evidenziate, nel corso delle sessioni di trattamento AMPS, le differenze statisticamente significative emerse da un precedente studio, sullo stesso database di pazienti, effettuato con misure mediante sistemi optoelettronici e prove di Gait Analysis. I risultati dello studio comparativo hanno evidenziato che nonostante il sensore inerziale non sia in grado di fornire risultati sempre così accurati e precisi in senso assoluto come quelli forniti da un sistema optoelettronico per l’analisi del movimento, permette di monitorare la condizione motoria generale di questi pazienti. E in ogni caso, vantaggi riferiti alla tecnologia economica, alla facilità di implementazione della procedura di calcolo in un contesto ambulatoriale, alla non invasività e la possibilità di ottenere dati quantitativi e oggettivi senza l’utilizzo di costose attrezzature di laboratorio, rendono questo sensore inerziale una possibile scelta in questo campo di analisi clinica. I risultati ottenuti tramite l’utilizzo dell’indice sintetico realizzato, infine, rispecchiano in buona parte i risultati conseguiti a seguito dello studio di Gait Analysis. Si può dunque ritenere che l’utilizzo di un indice sintetico di questo tipo possa considerarsi un metodo di valutazione accettabile, che in modo semplice ed immediato, permetta di dare un’indicazione approssimativa in merito al grado di freezing del soggetto in analisi.
Caratterizzazione del fenomeno del freezing nella malattia di Parkinson mediante sistemi indossabili
GRAMELLINI, BARBARA
2015/2016
Abstract
The study of postural and motor impairments in patients with motor problems can give very important information to know the level of functional limitations resulting to the pathology and its evolution overtime. Furthermore, it provides important elements to assessing the efficacy of rehabilitation for recovery of pathological impairments. It is therefore, important, for those patients able to make use of innovative techniques and advanced equipment that allow describing, quantifying and evaluating the movement. The clinical evaluation of the movement, especially of walking, it is realized in laboratories, where patients have to perform some motor tasks, which are detected by different type of sensors. There are, among these, optoelectronic systems, which allowed computerized, multifactorial and integrated analysis of spatio-temporal and kinematic parameters of the walking, along with the electromyoagraphic signals of the muscles under observation. Alongside the recognized and certified strumentations for gait analysis, in the last 10-15 years new, economic portable systems have been developed, which are configured as wearable inertial sensors. Parkinson’s disease (PD) is a neurodegenerative disorder that affects nerve cells in a part of the brain that controls muscle movement. Symptoms of Parkinson’s disease may include resting tremor, bradykinesia, rigidity, postural instability and freezing. Although not present in all patients, freezing is perhaps the most debilitating symptom of Parkinson’s disease as it may lead to falls, a decrease in quality of life and loss of independence. Freezing of Gait (FOG) is a paroxysmal phenomenon commonly seen as an advanced symptom in Parkinson’s disease. The FOG events are transient, generally lasting for a few seconds, tending to increase in frequency as the disease progresses. There are three different subtypes of FOG. The well-known clinical manifestation is that of a patient who suddenly becomes incapable to start walking or fails to continue to move forward (akinesia). The second subtypes of FOG is related to complete absence of movement, while the third subtypes of FOG consists of shuffling forward with very short steps. If gait and movement evaluation of the subjects with Parkinson's disease can be made in the Motion Analysis laboratories, as documented by several studies in the literature, there is a need to move towards a simpler evaluation , suited to the type of patient and the needs of the clinic. The quantitative gait analysis performed in a movement analysis laboratory present the advantages to be precise, accurate, repeatable and providing with reliable results. On the other hand, the gait itself can be altered by the restrictions due to the dimensions of the measurement system, especially in those patients in which the cognitive aspect greatly affects the motor pattern. Moreover, an analysis conducted in laboratory does not take into account subjects’ mobility throughout the day, week, month or longer term, and the dayby-day environment where they usually perform the gait. The main objective of this thesis is verify if it is possible to characterize the freezing episode in Parkinson’s diseases patients, using inertial sensors. First of all, the first step of the work was the accuracy rating of the inertial sensor (GSensor) compared to the gold standard (optoelectronic system); for this reason were recruited, at the Laboratory of Analysis of the movement of the Clinic San Raffaele, in Cassini, 14 patients with Parkinson’s diseases, 7 of these affected by freezing. The patients were subjected to walking trials acquired with the optoelectronic system and with the wearable inertial sensor. The variables analysis for the comparison focused on those identified by previous studies such as those designed to characterize the phenomenon of freezing and in particular spatio-temporal and gait regularity indices. Statical analysis helped to identify if the sensor is able, first, to accurately estimate the selected variables, and more if it is able to perceive the differences between the group with Parkinson’s diseases with freezing than the group of patients with Parkinson’s diseases but without freezing. Another aim of work is to define a forecasting model to estimate that could estimate a synthetic freezing index, based on the variables acquired through a wearable sensor. Doing this, were selected, according to specific inclusion criteria, 20 patients, all suffering from Parkinson's disease aggravated by freezing episodes. These patients had undergone to several walking trials, acquired with a wearable inertial devices, at the Laboratory of Movement Analysis of the Federal University of Health Sciences of Porto Alegre, in Brazil. Starting from the results obtained from the comparative study, have been selected the parameters to be entered into the forecasting model. Applying multiple linear regression analysis, the model was developed in order to obtain a synthetic index, which represents, with a unique number, the probability of occurrence of freezing, estimating the value of the FOG - Q scale. The last goal is to apply the identified index on the sample of 20 patients, who had undergone a rehabilitation treatment, based on Automated Mechanical Peripheral Stimulation (AMPS). In this context, the database has been divided into two subgroups of 10 subjects: while one group was treated with AMPS, the other has been treated with a placebo stimulation. A statistical analysis has determined if through this synthetic index it is possible to point out, during the AMPS treatment sessions, the statistically significant differences emerged from a previous study on the same patient database, carried out with measures using optoelectronic systems and tests of Gait Analysis . The data provided from the comparative study showed that although, G-Sensor is not able to produce results not always as much accurate and precise as those of a gold standard measurement system, it could be successfully be used in monitoring the general condition of a patient. Anyhow, all the advantages regarding as the cheap technology, the easy to implement procedure applicable in ambulatory contexts, non invasivity, ecology and possibility to get objective quantitative data without the expensive facilities of a movement analysis laboratory make G-sensor a very suitable choice in this field of clinical analysis. Finally, the results obtained with the synthetic index reflect the good results achieved from the Gait Analysis study. So this type of FOG index can be regarded as an acceptable method of evaluation that in a simple and immediate way allows giving an approximate indication regarding the freezing conditions of the subject in analysis.File | Dimensione | Formato | |
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Descrizione: Testo della tesi "caratterizzazione del fenomeno del freezing nella Malattia di Parkinson mediante sistemi indossabili"
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https://hdl.handle.net/10589/123090