Assessment of gait spatio-temporal parameters in neurological disorders using wearable inertial sensors

Movement analysis carried out in laboratory settings is a powerful, but costly solution since it requires dedicated instrumentation, space and personnel. Recently, new technologies such as the magnetic and inertial measurement units (MIMU) are becoming widely accepted as tools for the assessment of human motion in clinical and research settings. They are relatively easy-to-use and potentially suitable for estimating gait kinematic features, including spatio-temporal parameters. The objective of this thesis regards the development and testing in clinical contexts of robust MIMUs based methods for assessing gait spatio-temporal parameters applicable across a number of different pathological gait patterns. First, considering the need of a solution the least obtrusive as possible, the validity of the single unit based approach was explored. A comparative evaluation of the performance of various methods reported in the literature for estimating gait temporal parameters using a single unit attached to the trunk first in normal gait and then in different pathological gait conditions was performed. Then, the second part of the research headed towards the development of new methods for estimating gait spatio-temporal parameters using shank worn MIMUs on different pathological subjects groups. In addition to the conventional gait parameters, new methods for estimating the changes of the direction of progression were explored. Finally, a new hardware solution and relevant methodology for estimating inter-feet distance during walking was proposed. Results of the technical validation of the proposed methods at different walking speeds and along different paths against a gold standard were reported and showed that the use of two MIMUs attached to the lower limbs associated with a robust method guarantee a much higher accuracy in determining gait spatio-temporal parameters. In conclusion, the proposed methods could be reliably applied to various abnormal gaits obtaining in some cases a comparable level of accuracy with respect to normal gait

Gait Analysis Using Wearable Sensors

Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications

A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications

Gait analysis continues to be an important technique for many clinical applications to diagnose and monitor certain diseases. Many mental and physical abnormalities cause measurable differences in a person's gait. Gait analysis has applications in sport, computer games, physical rehabilitation, clinical assessment, surveillance, human recognition, modelling, and many other fields. There are established methods using various sensors for gait analysis, of which, accelerometers are one of the most often employed. Accelerometer sensors are generally more user friendly and less invasive. In this paper, we review research regarding accelerometer sensors used for gait analysis with particular focus on clinical applications. We provide a brief introduction to accelerometer theory followed by other popular sensing technologies. The commonly used gait phases and parameters are enumerated. The details of extracting the papers for review are provided. We also review several gait analysis software. Then, we provide an extensive report of accelerometry based gait analysis systems and applications with additional emphasis on trunk accelerometry. We conclude this review with future research directions

Gait monitoring: from the clinics to the daily life

Monitoring of gait in daily living allows a quantitative analysis of walking in unrestricted conditions, with many potential clinical applications. This thesis aims at addressing the limitations that still hinder the wider adoption of this approach in clinical practice, providing healthcare professionals and researchers new tools which may impact on current gait assessment procedures and improve the treatment of many diseases leading to – or generated by – mobility impairments. The thesis comprises four experimental sections: Accuracy of commercially-available devices. Step detection accuracy in currently available physical activity monitors was assessed in healthy individuals. The best performing device was then tested in multiple sclerosis patients, showing reliability but highly speed-dependent accuracy. These findings suggest that a short set of tests performed in controlled conditions could inform researchers before starting unsupervised monitoring of gait in patients. Differences between laboratory and free-living gait parameters. The study assessed the accuracy of two algorithms for gait event detection, and provided normative values of gait temporal parameters for healthy subjects in different environments and types of walking. A pilot study toward clinical application. This pilot study compared laboratory based tests with daily living assessment of gait features in multiple sclerosis patients. Results provided clear evidence that in this population clinical gait tests might not represent typical gait patterns of daily living. Analysis of free-living walking in patients with Diabetes. A systematic review is presented looking for evidence of the effectiveness of walking as physical activity to reduce inflammation. Then, cadence and step duration variability are examined during free-living walking in a group of patients with diabetes. This thesis systematically highlighted potential and actual limitations in the use of wearable sensors for gait monitoring in daily life, providing clear practical indications and normative values which are essential for the widespread informed and effective clinical adoption of this technology

Wearables for Movement Analysis in Healthcare

Quantitative movement analysis is widely used in clinical practice and research to investigate movement disorders objectively and in a complete way. Conventionally, body segment kinematic and kinetic parameters are measured in gait laboratories using marker-based optoelectronic systems, force plates, and electromyographic systems. Although movement analyses are considered accurate, the availability of specific laboratories, high costs, and dependency on trained users sometimes limit its use in clinical practice. A variety of compact wearable sensors are available today and have allowed researchers and clinicians to pursue applications in which individuals are monitored in their homes and in community settings within different fields of study, such movement analysis. Wearable sensors may thus contribute to the implementation of quantitative movement analyses even during out-patient use to reduce evaluation times and to provide objective, quantifiable data on the patients’ capabilities, unobtrusively and continuously, for clinical purposes

Recuperación de la marcha durante el primer año tras el ictus medido a través de acelerometría

INTRODUCCIÓN: La elevada incidencia del ictus, la frecuente cronicidad de sus secuelas y el impacto económico de la discapacidad provocada por el mismo ponen de manifiesto la necesidad de desarrollar una fisioterapia neurológica comunitaria respondiendo a criterios económicos, sociales y de salud. Desde la fisioterapia, la valoración de la marcha tras el ictus se caracteriza por estar restringida al ámbito clínico, por la subjetividad y por la falta de fiabilidad. Los acelerómetros ofrecen la posibilidad de monitorizar el movimiento en la comunidad de un modo objetivo, preciso, fiable, de bajo coste y sin ofrecer restricciones mecánicas para la deambulación. A pesar de los beneficios de la acelerometría, muy pocos estudios la han empleado para analizar en detalle diferentes aspectos del comportamiento durante la marcha tras el ictus. OBJETIVOS: Describir la recuperación de la marcha, en términos de cantidad, distribución y calidad de la misma a lo largo del primer año tras la lesión; analizar las correlaciones entre las variables de estudio y comparar los resultados obtenidos un año después del ictus con los del grupo control. MATERIAL Y MÉTODO: Diseño: para responder al primer objetivo se empleó un diseño longitudinal de seguimiento de la cohorte durante un año, para responder al segundo, se realizó un estudio descriptivo correlacional y para el tercero, un estudio de asociación cruzada. Muestra: 23 pacientes con ictus, reclutados con muestreo no probabilístico de conveniencia, y 20 sujetos sanos. Intervención: Se realizaron mediciones con acelerometría en la 1ª, la 12ª y la 48ª semana tras el ictus (T1, T2 y T3, respectivamente) y en un único momento en el grupo de individuos sanos, en el entorno habitual de los sujetos durante ochos horas al día, desde las 10 de la mañana hasta las 6 de la tarde. Variables de estudio: las variables de cantidad eran el tiempo de marcha, en bipedestación, en sedestación, en decúbito y de sedentarismo; los parámetros de distribución estaban constituidos por la duración media, el número y el coeficiente de variación de los periodos de marcha y el exponente de sedentarismo, y las variables de calidad fueron la regularidad del paso, la regularidad del ciclo, el índice de simetría, el ratio de duración del paso y la velocidad de marcha. RESULTADOS: El tiempo de marcha, de bipedestación, de sedentarismo y el número de periodos de marcha se incrementó de T1 a T2 (p0,58). El resto de variables de distribución no experimentaron cambios significativos a lo largo del año (p>0,30). La regularidad del ciclo longitudinal, el índice de simetría longitudinal y la velocidad de marcha mejoraron desde el momento inicial hasta el año tras la lesión (p<0,05). Se obtuvieron correlaciones moderadas-altas entre el tiempo en bipedestación y el número de periodos de marcha, entre tiempo de marcha y duración media de los periodos de marcha, entre el tiempo de marcha y la velocidad y entre la regularidad del paso y la velocidad de marcha. En T3, las variables de cantidad (a excepción del tiempo en decúbito y de sedentarismo) y las de distribución alcanzaron niveles similares a los del grupo control, mientras que la regularidad del paso y la velocidad de marcha mostraban diferencias significativas (p<0,02). CONCLUSIONES: Las dimensiones de la marcha estudiadas en esta cohorte mostraron diferentes patrones de recuperación tras el ictus y alcanzaron niveles desiguales al compararlos con el grupo de individuos sanos de referencia. A través de la descripción de aspectos como la cantidad, distribución y calidad de la deambulación en personas con ictus, los fisioterapeutas podrán incrementar su conocimiento sobre la patología del paciente y ajustar de forma precisa e individualizada los objetivos, la dosificación y elección del tratamiento en el entorno habitual de los pacientes.INTRODUCTION: The high incidence, chronic sequelae and economic impact of stroke highlights the need to develop a neurological physiotherapy in the community, according to financial, social and health purposes. Physical therapy gait assessment has commonly been performed in clinical standardized settings, with subjective tools. Accelerometers offers the possibility of monitoring human movement objectively in the community, with some advantages including the low-cost, high accuracy and reliability and their small size which enables subjects to walk relatively unrestricted. In spite of the benefits of accelerometry, only a few studies have comprehensively examined different aspects of walking behavior among stroke patients. OBJECTIVES: The purpose of this study was to describe the course of different dimensions of walking behaviour, in terms of amount, distribution and quality, over a period of one year following stroke, using accelerometry; to explore the mutual relationships between main outcomes measures, and to compare the patient data one year after stroke with a healthy group. METHODS: Design: related to the first objective, we performed a one-year follow-up cohort study, in relation with the second objective the design was a correlational study and, with regard to the third objective, we used a repeated-measures design. Participants: A total of 23 stroke patients, recruited with a non-probability convenience sampling, and 20 age-matched healthy subjects were included in the study. Intervention: Accelerometer assessments were made in the participants’ daily environment for 8 h/day during the 1st (T1), 12th (T2) and 48th (T3) weeks after stroke, and at one time-point in healthy subjects. Main outcomes measures: percentage of time walking, time upright, time sitting, time lying and sedentary time (amount aspect); mean duration and number of walking periods, walking coefficient of variation and sedentary exponent (distribution aspect), step and stride regularity, step and stride symmetry, step-time ratio and walking speed (quality aspect). RESULTS: Time walking, time upright and number of walking bouts increased during T1 and T2 (p0.58). The rest of distribution variables showed no significant improvements (p>0.30) during all phases. Stride regularity longitudinal, gait symmetry longitudinal and gait speed increased significantly from T1 to T3. Moderate to high correlations were found between upright time and number of walking periods; walking time and mean duration of walking periods; walking time and gait speed and between step regularity and gait speed. At T3, amount and distribution variables (except for time lying and sedentary time) reached the level of the healthy group, but significant differences remained (p<0.02) in step regularity and gait speed. CONCLUSIONS: In this cohort, different outcomes of walking behavior, represented by amount, distribution and quality parameters of gait, showed different patterns and levels of recovery during the first year post-stroke. Describing these aspects of walking may help physical therapists to understand stroke patients’ motor problems, to establish tailored therapeutic objectives and to choose the appropriate dose and treatment in patients’ natural environment

Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review

In adults 65 years or older, falls or other neuromotor dysfunctions are often framed as walking-related declines in motor skill; the frequent occurrence of such decline in walking-related motor skill motivates the need for an improved understanding of the motor skill of walking. Simple gait measurements, such as speed, do not provide adequate information about the quality of the body motion’s translation during walking. Gait measures from accelerometers can enrich measurements of walking and motor performance. This review article will categorize the aspects of the motor skill of walking and review how trunk-acceleration gait measures during walking can be mapped to motor skill aspects, satisfying a clinical need to understand how well accelerometer measures assess gait. We will clarify how to leverage more complicated acceleration measures to make accurate motor skill decline predictions, thus furthering fall research in older adults

Development of a real-time classifier for the identification of the Sit-To-Stand motion pattern

The Sit-to-Stand (STS) movement has significant importance in clinical practice, since it is an indicator of lower limb functionality. As an optimal trade-off between costs and accuracy, accelerometers have recently been used to synchronously recognise the STS transition in various Human Activity Recognition-based tasks. However, beyond the mere identification of the entire action, a major challenge remains the recognition of clinically relevant phases inside the STS motion pattern, due to the intrinsic variability of the movement. This work presents the development process of a deep-learning model aimed at recognising specific clinical valid phases in the STS, relying on a pool of 39 young and healthy participants performing the task under self-paced (SP) and controlled speed (CT). The movements were registered using a total of 6 inertial sensors, and the accelerometric data was labelised into four sequential STS phases according to the Ground Reaction Force profiles acquired through a force plate. The optimised architecture combined convolutional and recurrent neural networks into a hybrid approach and was able to correctly identify the four STS phases, both under SP and CT movements, relying on the single sensor placed on the chest. The overall accuracy estimate (median [95% confidence intervals]) for the hybrid architecture was 96.09 [95.37 - 96.56] in SP trials and 95.74 [95.39 \u2013 96.21] in CT trials. Moreover, the prediction delays ( 4533 ms) were compatible with the temporal characteristics of the dataset, sampled at 10 Hz (100 ms). These results support the implementation of the proposed model in the development of digital rehabilitation solutions able to synchronously recognise the STS movement pattern, with the aim of effectively evaluate and correct its execution

Study and development of sensorimotor interfaces for robotic human augmentation

This thesis presents my research contribution to robotics and haptics in the context of human augmentation. In particular, in this document, we are interested in bodily or sensorimotor augmentation, thus the augmentation of humans by supernumerary robotic limbs (SRL). The field of sensorimotor augmentation is new in robotics and thanks to the combination with neuroscience, great leaps forward have already been made in the past 10 years. All of the research work I produced during my Ph.D. focused on the development and study of fundamental technology for human augmentation by robotics: the sensorimotor interface. This new concept is born to indicate a wearable device which has two main purposes, the first is to extract the input generated by the movement of the user's body, and the second to provide the somatosensory system of the user with an haptic feedback. This thesis starts with an exploratory study of integration between robotic and haptic devices, intending to combine state-of-the-art devices. This allowed us to realize that we still need to understand how to improve the interface that will allow us to feel the agency when using an augmentative robot. At this point, the path of this thesis forks into two alternative ways that have been adopted to improve the interaction between the human and the robot. In this regard, the first path we presented tackles two aspects conerning the haptic feedback of sensorimotor interfaces, which are the choice of the positioning and the effectiveness of the discrete haptic feedback. In the second way we attempted to lighten a supernumerary finger, focusing on the agility of use and the lightness of the device. One of the main findings of this thesis is that haptic feedback is considered to be helpful by stroke patients, but this does not mitigate the fact that the cumbersomeness of the devices is a deterrent to their use. Preliminary results here presented show that both the path we chose to improve sensorimotor augmentation worked: the presence of the haptic feedback improves the performance of sensorimotor interfaces, the co-positioning of haptic feedback and the input taken from the human body can improve the effectiveness of these interfaces, and creating a lightweight version of a SRL is a viable solution for recovering the grasping function

Proceedings XXII Congresso SIAMOC 2022

Il congresso annuale della Società Italiana di Analisi del Movimento in Clinica dà l’occasione a tutti i professionisti, dell’ambito clinico e ingegneristico, di incontrarsi, presentare le proprie ricerche e rimanere aggiornati sulle più recenti innovazioni nell’ambito dell’applicazione clinica dei metodi di analisi del movimento, al fine di promuoverne lo studio e le applicazioni cliniche per migliorare la valutazione dei disordini motori, aumentare l’efficacia dei trattamenti attraverso l’analisi quantitativa dei dati e una più focalizzata pianificazione dei trattamenti, ed inoltre per quantificare i risultati delle terapie correnti