A functional calibration protocol for ankle plantar-dorsiflexion estimate using magnetic and inertial measurement units: Repeatability and reliability assessment

The ankle joint complex presents a tangled functional anatomy, which understanding is fundamental to effectively estimate its kinematics on the sagittal plane. Protocols based on the use of magnetic and inertial measurement units (MIMUs) currently do not take in due account this factor. To this aim, a joint coordinate system for the ankle joint complex is proposed, along with a protocol to perform its anatomical calibration using MIMUs, consisting in a combination of anatomical functional calibrations of the tibiotalar axis and static acquisitions. Protocol repeatability and reliability were tested according to the metrics proposed in Schwartz et al. (2004) involving three different operators performing the protocol three times on ten participants, undergoing instrumented gait analysis through both stereophotogrammetry and MIMUs. Instrumental reliability was evaluated comparing the MIMU-derived kinematic traces with the stereophotogrammetric ones, obtained with the same protocol, through the linear fit method. A total of 270 gait cycles were considered. Results showed that the protocol was repeatable and reliable for what concerned the operators (0.4 +/- 0.4 deg and 0.8 +/- 0.5 deg, respectively). Instrumental reliability analysis showed a mean RMSD of 3.0 +/- 1.3 deg, a mean offset of 9.4 +/- 8.4 deg and a mean linear relationship strength of R2 = 0.88 +/- 0.08. With due caution, the protocol can be considered both repeatable and reliable. Further studies should pay attention to the other ankle degrees of freedom as well as on the angular convention to compute them

Using magneto-inertial-measurement-units to track upper-limb movement during rehabilitation

Functional Electrical Stimulation (FES) can be used to support upper-limb rehabilitation after a stroke. A key aspect of FES control and also patient monitoring is the automatic tracking of upper-limb motion during intensive and functional practise of upper-limb tasks. To achieve this in a home environment, simple on-body sensors are required. A promising approach is to use Magnetic and Inertial Measurement Units (MIMUs), but they provide body-segment orientations rather than anatomical joint angles, the latter being more meaningful. To solve this problem the sensor orientation data must be interpreted anatomically, which requires that for each body-segment the orientation of its sensor coordinate frame is known with respect to its anatomical coordinate frame. Therefore, appropriate calibration must be performed to obtain the relationship between each sensor frame and its corresponding body-segment anatomical frame.While many papers have been published on anatomical calibration methods for MIMUs, there has been no comprehensive comparison of the alternative approaches to establish their relative merits. For FES supported upper-limb therapy, the need is for simple and fast donning and calibration, whilst achieving acceptable accuracy and repeatability with regards to the calculated joint kinematics. Therefore, the main objective of the PhD research was to undertake such a comparison and make recommendations for donning and calibration for the purposes of upper-limb FES.To address this problem the PhD work included:1. Undertaking a comprehensive and critical comparison of alternative anatomical calibration methods for MIMUs in terms of accuracy, speed, and simplicity.2. Finding the most appropriate anatomical calibration methods for use in upper-limb FES applications with stroke patients.3. Determining the best methods for processing MIMU outputs to provide anatomically meaningful upper-limb kinematic data.4. Experimentally assessing these methods against a gold standard (a VICON optical motion capture system).The results demonstrate that there is considerable variation between the alternative sensor defined anatomical frames and, hence, confirm the need for comprehensive comparisons. The comparisons reported in this thesis have led to tentative recommendations. Nevertheless, the methods reported are a sound foundation for future work to provide stronger recommendations, with more formal measures of confidence

Contributions to physical exercises monitoring with inertial measurement units

Resumen: La monitorización de movimientos trata de obtener información sobre su ejecución, siendo esencial en múltiples aplicaciones, como el seguimiento de terapias físicas. La monitorización tiene un doble objetivo esencial para lograr los beneficios de dichas terapias: asegurar la corrección en la ejecución de movimientos y mejorar la adherencia a los programas prescritos. Para lograr esta monitorización de forma remota y poco intrusiva, se necesitan recursos tecnológicos. Este trabajo se centra en las soluciones basadas en sensores inerciales. Esta tesis estudia los algoritmos de la literatura para el análisis de movimientos con sensores inerciales, determinando un parámetro anatómico requerido en diversas propuestas: la posición de las articulaciones respecto de los sensores, así como longitud de los segmentos anatómicos. En este trabajo se introducen dos algoritmos de calibración anatómica. El primero, basado en mínimos cuadrados, determina el punto o el eje medios de aceleración nula presente en las articulaciones fijas. El algoritmo está adaptado a los movimientos lentos dados en los miembros inferiores para estabilizar las articulaciones. El segundo, adaptado a la variación de la posición relativa del punto de aceleración nula respecto de los sensores a causa del característico tejido blando asociado al cuerpo humano, emplea las medidas inerciales como entradas en un filtro de Kalman extendido. Por otro lado, esta tesis aborda la falta de datos comunes para la evaluación y comparación de los algoritmos. Para ello, se diseña y crea una base de datos centrada en movimientos habituales en rutinas físicas, que se encuentra publicada en Zenodo. Esta base de datos contiene movimientos de calibración articular y de ejercicios de miembros inferiores y superiores ejecutados de forma correcta e incorrecta por 30 voluntarios de ambos sexos con un amplio rango de edades, grabados con cuatro sensores inerciales y un sistema de referencia óptico de alta precisión. Además, las grabaciones se encuentran etiquetadas acorde al tipo de ejercicio realizado y su evaluación. Finalmente, se estudia un segundo enfoque de monitorización de rutinas físicas, cuyo objetivo es reconocer y evaluar simultáneamente los ejercicios ejecutados, retos comúnmente estudiados individualmente. Se proponen tres sistemas que emplean las medidas de cuatro sensores inerciales y difieren en el nivel de detalle en las salidas del sistema. Para realizar las clasificaciones propuestas, se evalúan seis algoritmos de machine learning determinando el más adecuado.This thesis is framed in the field of remote motion monitoring, which aims to obtain information about the execution of movements. This information is essential in many applications, including the clinical ones, to measure the evolution of patients, to assess possible pathologies, such as motor or cognitive ones, and to follow up physical therapies. The monitoring of physical therapies has twofold purpose: to ensure the correct execution of movements and to improve adherence to the programs. Both purposes are essential to achieve the benefits associated with physical therapies. To accomplish this monitoring in a remote and non-intrusive way, technological resources such as the well-known inertial sensors are needed, which are commonly integrated into the so-called wearables. This work focuses on inertial-based solutions for monitoring physical therapy routines. However, the results of this work are not exclusive of this field, being able to be applied in other fields that require a motion monitoring. This work is intended to meet the needs of the monitoring systems found in the literature. In the review of previous proposals for remote monitoring of rehabilitation routines, we found two different main approaches. The first one is based on the analysis of movements, which estimates kinematic parameters, and the second one focuses on the qualitative characterization of the movements. From this differentiation, we identify and contribute to the limitations of each approach. With regard to the motion analysis for the estimation of kinematic parameters, we found an anatomical parameter required in various methods proposed in the literature. This parameter consists in the position of the joints with respect to the sensors, and sometimes these methods also require the length of the anatomical segments. The determination of these internal parameters is complex and is usually performed in controlled environments with optical systems or through palpation of anatomical landmarks by trained personnel. There is a lack of algorithms that determine these anatomical parameters using inertial sensors. This work introduces an algorithm for this anatomical calibration, which is based on the determination of the point of zero acceleration present in fixed joints. We use one inertial sensor per joint in order to simplify the complexity of algorithms versus using xv xvi ABSTRACT more than one. Since the relative position of this point may vary due to soft tissue movements or joint motion, the mean null acceleration point for the calibration motion is estimated by least squares. This algorithm is adapted to slow movements occurring in the lower-limbs to meet the required joint stabilization. Moreover, it can be applied to both joint centers and axes, although the latter is more complex to determine. Since we are dealing with the calibration of a system as complex as the human body, we evaluate different movements and their relation to the accuracy of the proposed system. This thesis also proposes a second, more versatile calibration method, which is adapted to the characteristic soft tissue associated with the human body. This method is based on the measurements of one inertial sensors used as inputs of an extended Kalman filter. We test the proposal both in synthetic data and in the real scenario of hip center of rotation determination. In simulations it provides an accuracy of 3% and in the real scenario, where the reference is obtained with a high precision optical system, the accuracy is 10 %. In this way, we propose a novel algorithm that localizes the joints adaptively to the motion of the tissues. In addition, this work addresses another limitation of motion analysis which is the lack of common datasets for the evaluation of algorithms and for the development of new proposals of motion monitoring methods. For this purpose, we design and create a public database focused on common movements in rehabilitation routines. Its design takes into account the joint calibration that is usually considered for the monitoring of joint parameters, performing functional movements for it. We monitor lower and upper limb exercises correctly and incorrectly performed by 30 volunteers of both sexes and a wide range of ages. One of the main objectives to be fulfilled by this database is the validation of algorithms based on inertial systems. Thus, it is recorded by using four inertial systems placed on different body limbs and including a highly accurate reference system based on infrared cameras. In addition, the recorded movements are labeled according to their characterization, which is based on the type of exercise performed and their quality. We provide a total of 7 076 files of inertial kinematic data with a high-precision reference, characterized with respect to the kind of performed motion and their correctness in performance, together with a function for automatic processing. Finally, we focus on the analysis of the second approach of monitoring physical routines, whose objective is to obtain qualitative information of their execution. This work contributes to the characterization of movements including their recognition and evaluation, which are usually studied separately. We propose three classification systems which use four inertial sensors. The proposals differ in the distribution of data and, therefore, the level of detail in the system outputs. We evaluate six machine learning techniques for the proposed classification systems in order to determine the most suitable for each of them: Support Vector Machines, Decision Trees, Random Forest, xvii K Nearest Neighbors, Extreme Learning Machines and Multi-Layer Perceptron. The proposals result in accuracy, F1-value, precision and sensitivity above the 88 %. Furthermore, we achieve a system with an accuracy of 95% in the complete qualitative characterization of the motions, which recognizes the performed motion and evaluates the correctness of its performance. It is worth highlighting that the highest metrics are always obtained with Support Vector Machines, among all the methods evaluated. The proposed classifier that provides the highest metrics is the one divided into two stages, that first recognizes the exercises and then evaluates them, compared with the other proposals that perform both tasks in one single-stage classification. From our work, it can be concluded that inertial systems are appropriate for remote physical exercise monitoring. On the one hand, they are suitable for the calibration of human joints necessary for various methods of motion analysis using one inertial sensor per joint. These sensors allow to obtain the estimation of an average joint location as well as the average length of anatomical segments. Also, joint centers can be located in scenarios where joint-related sensor movements occur, associated with soft tissue movement. On the other hand, a complete characterization of the physical exercises performed can be achieved with four inertial sensors and the appropriate algorithms. In this way, anatomical information can be obtained, as well as quantitative and qualitative information on the execution of physical therapies through the use of inertial sensors

Proceedings XXI Congresso SIAMOC 2021

XXI Congresso Annuale della SIAMOC, modalità telematica il 30 settembre e il 1° ottobre 2021. Come da tradizione, il congresso vuole essere un’occasione di arricchimento e mutuo scambio, dal punto di vista scientifico e umano. Verranno toccati i temi classici dell’analisi del movimento, come lo sviluppo e l’applicazione di metodi per lo studio del movimento nel contesto clinico, e temi invece estremamente attuali, come la teleriabilitazione e il telemonitoraggio

Assessing residual neck mobility when wearing a cervical orthosis: an application in patients with Motor Neurone Disease

Severe weakness of the neck extensor muscles has been observed in neuromuscular pathologies, such as motor neurone disease (MND). This condition reduces the ability to perform daily activities and communicate, leading to the adoption of a cervical orthosis. However, commercially available devices are designed to immobilize the neck, which makes them uncomfortable and strenuous to wear for a long time. The lack of a device specifically designed for those patients led to the development of the Sheffield Support Snood (SSS) which enables to adjust the support given to the head, according to the task performed and to the disease progression. The following step toward the SSS commercialisation and adoption was an objective evaluation of its performance and the assessment with the end users, which was the aim of this thesis. To this purpose, an experimental protocol designed to quantitatively assess neck mobility when wearing cervical orthoses, has been developed. This protocol and the associated signal processing techniques proved to be suitable for the assessment of neck mobility through the measurement of head movements, both in laboratory and clinical settings. After having quantitatively assessed head movement limitation in MND patients, filling an existing gap in the current literature, the effects of the SSS were tested. Compared to controls, patients presented an overall impaired ability to perform head movements in terms of reduced velocity (mean values between 27% and 41% lower in movements performed reaching the maximum range of motion and between 34% and 48% lower in movements performed reaching the maximum angular velocity), reduced smoothness (mean values between 21% and 44% lower in movements performed reaching the maximum range of motion) and increased presence of coupled movements (mean values between 37% and 58% higher in movements performed reaching the maximum range of motion and between 44% and 53% in movements performed reaching the maximum angular velocity). The SSS was effective in facilitating the head movements in MND patients. Among those 9 individuals that were fitted with anterior or anterior plus lateral supports 5 of them had a reduced presence on coupled movements in at least one of the movements performed. However, a proper fitting of the orthosis appeared crucial and in the future it should be based on a quantitative approach similar to the one developed in this thesis. This study paved the way for improvements in the SSS design and for future quantitative assessment of the characteristics of motor control and movement strategies in MND patients and of how these change when using a device aiming at compensating for functional impairments

Upper-limb Kinematic Analysis and Artificial Intelligent Techniques for Neurorehabilitation and Assistive Environments

Stroke, one of the leading causes of death and disability around the world, usually affects the motor cortex causing weakness or paralysis in the limbs of one side of the body. Research efforts in neurorehabilitation technology have focused on the development of robotic devices to restore motor and cognitive function in impaired individuals, having the potential to deliver high-intensity and motivating therapy. End-effector-based devices have become an usual tool in the upper- limb neurorehabilitation due to the ease of adapting to patients. However, they are unable to measure the joint movements during the exercise. Thus, the first part of this thesis is focused on the development of a kinematic reconstruction algorithm that can be used in a real rehabilitation environment, without disturbing the normal patient-clinician interaction. On the basis of the algorithm found in the literature that presents some instabilities, a new algorithm is developed. The proposed algorithm is the first one able to online estimate not only the upper-limb joints, but also the trunk compensation using only two non-invasive wearable devices, placed onto the shoulder and upper arm of the patient. This new tool will allow the therapist to perform a comprehensive assessment combining the range of movement with clinical assessment scales. Knowing that the intensity of the therapy improves the outcomes of neurorehabilitation, a ‘self-managed’ rehabilitation system can allow the patients to continue the rehabilitation at home. This thesis proposes a system to online measure a set of upper-limb rehabilitation gestures, and intelligently evaluates the quality of the exercise performed by the patients. The assessment is performed through the study of the performed movement as a whole as well as evaluating each joint independently. The first results are promising and suggest that this system can became a a new tool to complement the clinical therapy at home and improve the rehabilitation outcomes. Finally, severe motor condition can remain after rehabilitation process. Thus, a technology solution for these patients and people with severe motor disabilities is proposed. An intelligent environmental control interface is developed with the ability to adapt its scan control to the residual capabilities of the user. Furthermore, the system estimates the intention of the user from the environmental information and the behavior of the user, helping in the navigation through the interface, improving its independence at home.El accidente cerebrovascular o ictus es una de las causas principales de muerte y discapacidad a nivel mundial. Normalmente afecta a la corteza motora causando debilidad o parálisis en las articulaciones del mismo lado del cuerpo. Los esfuerzos de investigación dentro de la tecnología de neurorehabilitación se han centrado en el desarrollo de dispositivos robóticos para restaurar las funciones motoras y cognitivas en las personas con esta discapacidad, teniendo un gran potencial para ofrecer una terapia de alta intensidad y motivadora. Los dispositivos basados en efector final se han convertido en una herramienta habitual en la neurorehabilitación de miembro superior ya que es muy sencillo adaptarlo a los pacientes. Sin embargo, éstos no son capaces de medir los movimientos articulares durante la realización del ejercicio. Por tanto, la primera parte de esta tesis se centra en el desarrollo de un algoritmo de reconstrucción cinemática que pueda ser usado en un entorno de rehabilitación real, sin perjudicar a la interacción normal entre el paciente y el clínico. Partiendo de la base que propone el algoritmo encontrado en la literatura, el cual presenta algunas inestabilidades, se ha desarrollado un nuevo algoritmo. El algoritmo propuesto es el primero capaz de estimar en tiempo real no sólo las articulaciones del miembro superior, sino también la compensación del tronco usando solamente dos dispositivos no invasivos y portátiles, colocados sobre el hombro y el brazo del paciente. Esta nueva herramienta permite al terapeuta realizar una valoración más exhaustiva combinando el rango de movimiento con las escalas de valoración clínicas. Sabiendo que la intensidad de la terapia mejora los resultados de la recuperación del ictus, un sistema de rehabilitación ‘auto-gestionado’ permite a los pacientes continuar con la rehabilitación en casa. Esta tesis propone un sistema para medir en tiempo real un conjunto de gestos de miembro superior y evaluar de manera inteligente la calidad del ejercicio realizado por el paciente. La valoración se hace a través del estudio del movimiento ejecutado en su conjunto, así como evaluando cada articulación independientemente. Los primeros resultados son prometedores y apuntan a que este sistema puede convertirse en una nueva herramienta para complementar la terapia clínica en casa y mejorar los resultados de la rehabilitación. Finalmente, después del proceso de rehabilitación pueden quedar secuelas motoras graves. Por este motivo, se propone una solución tecnológica para estas personas y para personas con discapacidades motoras severas. Así, se ha desarrollado una interfaz de control de entorno inteligente capaz de adaptar su control a las capacidades residuales del usuario. Además, el sistema estima la intención del usuario a partir de la información del entorno y el comportamiento del usuario, ayudando en la navegación a través de la interfaz, mejorando su independencia en el hogar

Motor Ability Assessment in Lower-Limb Amputees

This work investigates the necessary aspects for the motor ability assessment in persons with lower-limb amputation, following the evaluation approaches suggested by the World Health Organization. In the specific case of the lower-limb amputee patient, the assessement can be articulated on two different levels: a first general, concerning the motor ability and quality of life as a function of that (level of independence), and a second local one, concerning the specificity of each single prosthetic module which composes the entire prosthetic chain, in the relationship with the user's motor function. The general purpose is therefore to provide fact-finding and operational tools in order to identify an accurate and reliable methodology for the motor ability assessment of prosthetized lower-limb amputees, both during gait and stereotypic locomotor tasks. This methodology is intended to constitute a valid and conventionally recognized reference for the amputee rehabilitation team, both for the functional patient assessment and for the technical-clinical evaluation of the prosthetic modules used. The perspective purpose is to verify the extractability of parameters particulary sensitive to the variability of clinical aspects related to the the lower-limb amputee motor ability, that can therefore be measured by a simple, low cost, wearable instrumentation, making them intelligible and useful to the clinical team and exportable in a remote supervision context. The main aims of the present thesis can be summarized in: 1. Identification of parameters of evaluation sensitive to the motor ability changes in lower-limb amputee subjects; 2. Definition of experimental methodological protocols ad hoc for the functional evaluation of the subject and for the appropriateness of the single prosthetic components. The research activity of the present thesis has been oriented on different works, each of which presents various peculiar aspects for the identification of specific indices for the assessment of the lower-limb amputee’s motor ability