Deep Learning Based Abnormal Gait Classification System Study with Heterogeneous Sensor Network

Gait is one of the important biological characteristics of the human body. Abnormal gait is mostly related to the lesion site and has been demonstrated to play a guiding role in clinical research such as medical diagnosis and disease prevention. In order to promote the research of automatic gait pattern recognition, this paper introduces the research status of abnormal gait recognition and systems analysis of the common gait recognition technologies. Based on this, two gait information extraction methods, sensor-based and vision-based, are studied, including wearable system design and deep neural network-based algorithm design. In the sensor-based study, we proposed a lower limb data acquisition system. The experiment was designed to collect acceleration signals and sEMG signals under normal and pathological gaits. Specifically, wearable hardware-based on MSP430 and upper computer software based on Labview is designed. The hardware system consists of EMG foot ring, high-precision IMU and pressure-sensitive intelligent insole. Data of 15 healthy persons and 15 hemiplegic patients during walking were collected. The classification of gait was carried out based on sEMG and the average accuracy rate can reach 92.8% for CNN. For IMU signals five kinds of abnormal gait are trained based on three models: BPNN, LSTM, and CNN. The experimental results show that the system combined with the neural network can classify different pathological gaits well, and the average accuracy rate of the six-classifications task can reach 93%. In vision-based research, by using human keypoint detection technology, we obtain the precise location of the key points through the fusion of thermal mapping and offset, thus extracts the space-time information of the key points. However, the results show that even the state-of-the-art is not good enough for replacing IMU in gait analysis and classification. The good news is the rhythm wave can be observed within 2 m, which proves that the temporal and spatial information of the key points extracted is highly correlated with the acceleration information collected by IMU, which paved the way for the visual-based abnormal gait classification algorithm.步态指人走路时表现出来的姿态，是人体重要生物特征之一。异常步态多与病变部位有关，作为反映人体健康状况和行为能力的重要特征，其被论证在医疗诊断、疾病预防等临床研究中具有指导作用。为了促进步态模式自动识别的研究，本文介绍了异常步态识别的研究现状，系统地分析了常见步态识别技术以及算法，以此为基础研究了基于传感器与基于视觉两种步态信息提取方法，内容包括可穿戴系统设计与基于深度神经网络的算法设计。 在基于传感器的研究中，本工作开发了下肢步态信息采集系统，并利用该信息采集系统设计实验，采集正常与不同病理步态下的加速度信号与肌电信号，搭建深度神经网络完成分类任务。具体的，在系统搭建部分设计了基于MSP430的可穿戴硬件设备以及基于Labview的上位机软件，该硬件系统由肌电脚环，高精度IMU以及压感智能鞋垫组成，该上位机软件接收、解包蓝牙数据并计算出步频步长等常用步态参数。 在基于运动信号与基于表面肌电的研究中，采集了15名健康人与15名偏瘫病人的步态数据，并针对表面肌电信号训练卷积神经网络进行帕金森步态的识别与分类，平均准确率可达92.8%。针对运动信号训练了反向传播神经网络，LSTM以及卷积神经网络三种模型进行五种异常步态的分类任务。实验结果表明，本工作中步态信息采集系统结合神经网络模型，可以很好地对不同病理步态进行分类，六分类平均正确率可达93%。 在基于视觉的研究中，本文利用人体关键点检测技术，首先检测出图片中的一个或多个人，接着对边界框做图像分割，接着采用全卷积resnet对每一个边界框中的人物的主要关节点做热力图并分析偏移量，最后通过热力图与偏移的融合得到关键点的精确定位。通过该算法提取了不同步态下姿态关键点时空信息，为基于视觉的步态分析系统提供了基础条件。但实验结果表明目前最高准确率的人体关键点检测算法不足以替代IMU实现步态分析与分类。但在2m之内可以观察到节律信息，证明了所提取的关键点时空信息与IMU采集的加速度信息呈现较高相关度，为基于视觉的异常步态分类算法铺平了道路

Smart Technology for Telerehabilitation: A Smart Device Inertial-sensing Method for Gait Analysis

The aim of this work was to develop and validate an iPod Touch (4th generation) as a potential ambulatory monitoring system for clinical and non-clinical gait analysis. This thesis comprises four interrelated studies, the first overviews the current available literature on wearable accelerometry-based technology (AT) able to assess mobility-related functional activities in subjects with neurological conditions in home and community settings. The second study focuses on the detection of time-accurate and robust gait features from a single inertial measurement unit (IMU) on the lower back, establishing a reference framework in the process. The third study presents a simple step length algorithm for straight-line walking and the fourth and final study addresses the accuracy of an iPod’s inertial-sensing capabilities, more specifically, the validity of an inertial-sensing method (integrated in an iPod) to obtain time-accurate vertical lower trunk displacement measures. The systematic review revealed that present research primarily focuses on the development of accurate methods able to identify and distinguish different functional activities. While these are important aims, much of the conducted work remains in laboratory environments, with relatively little research moving from the “bench to the bedside.” This review only identified a few studies that explored AT’s potential outside of laboratory settings, indicating that clinical and real-world research significantly lags behind its engineering counterpart. In addition, AT methods are largely based on machine-learning algorithms that rely on a feature selection process. However, extracted features depend on the signal output being measured, which is seldom described. It is, therefore, difficult to determine the accuracy of AT methods without characterizing gait signals first. Furthermore, much variability exists among approaches (including the numbers of body-fixed sensors and sensor locations) to obtain useful data to analyze human movement. From an end-user’s perspective, reducing the amount of sensors to one instrument that is attached to a single location on the body would greatly simplify the design and use of the system. With this in mind, the accuracy of formerly identified or gait events from a single IMU attached to the lower trunk was explored. The study’s analysis of the trunk’s vertical and anterior-posterior acceleration pattern (and of their integrands) demonstrates, that a combination of both signals may provide more nuanced information regarding a person’s gait cycle, ultimately permitting more clinically relevant gait features to be extracted. Going one step further, a modified step length algorithm based on a pendulum model of the swing leg was proposed. By incorporating the trunk’s anterior-posterior displacement, more accurate predictions of mean step length can be made in healthy subjects at self-selected walking speeds. Experimental results indicate that the proposed algorithm estimates step length with errors less than 3% (mean error of 0.80 ± 2.01cm). The performance of this algorithm, however, still needs to be verified for those suffering from gait disturbances. Having established a referential framework for the extraction of temporal gait parameters as well as an algorithm for step length estimations from one instrument attached to the lower trunk, the fourth and final study explored the inertial-sensing capabilities of an iPod Touch. With the help of Dr. Ian Sheret and Oxford Brookes’ spin-off company ‘Wildknowledge’, a smart application for the iPod Touch was developed. The study results demonstrate that the proposed inertial-sensing method can reliably derive lower trunk vertical displacement (intraclass correlations ranging from .80 to .96) with similar agreement measurement levels to those gathered by a conventional inertial sensor (small systematic error of 2.2mm and a typical error of 3mm). By incorporating the aforementioned methods, an iPod Touch can potentially serve as a novel ambulatory monitor system capable of assessing gait in clinical and non-clinical environments

Understanding the modulation of walking speed and exploring how this differs in people with Parkinson’s disease.

Background: Parkinson's disease (PD) affects the ability of individuals to initiate movement and change muscle activity during gait initiation (GI) and during variations in walking speed. The present study aims to investigate the biomechanics parameters (kinetics and kinematics) and muscle activity characteristics during GI and variation in speed while walking on a treadmill and overground (OG) for PD-affected individuals and physically fit people. Methods: In this study, participants (n=17) included a physical fit (n= 11, aged 31.72 +/17.91 years) and a Parkinson’s (n= 6, aged 67.33 +/-11.57 years, disease duration 13.5 +/8.69). Both groups were evaluated while walking on the treadmill and over the ground for two phases. The first phase was Gait initiation, where the participants were asked to start walking at their comfortable speed for two gait cycles on the treadmill and OG. The second phase was speed variation, where the participants also walked at their comfortable speed, and increased their speed in response to visual instruction on screen. However, on the ground, they were asked to change their speed after their fifth walking step. A self-pacing treadmill synchronised with a virtual reality screen (MotekMedical, the Netherlands) and A 12-camera motion capture system (Vicon Motion Systems, UK) integrated with two embedded force plates and a wireless EMG system (Trigno, Delsys, USA) collected the biomechanical and muscle excitation data. Three gait cycles; before, during and immediately after the speed change was used for the analysis of the speed variation. Data were limited to lower limb joints and three muscles (tibialis anterior, gastrocnemius and soleus. Differences in the percentage of contraction and magnitude of muscle activation (area under the curve, AUC) were compared before and during the speed change. Results: PD-affected individuals spent less time on GI during treadmill walking (2.06 s ± 0.39) than the healthy reference group (2.25 s ± 0.42) but more time with OG walking (1.95s ±0.25) compared to the reference group (1.49s ±0.56). The reference group had a greater range of lower limb joint movement than the PD group during GI on both walking surfaces. The power produced at the hip and ankle joint by the reference group was higher than the overall PD group. The magnitude of muscle activation was lower in the PD group than the reference group, and the severity of the disease affected the magnitude of the muscle activation. At speed variation, both the reference and PD groups showed an increase in speed. Cadence declined in the reference group but elevated in the PD group. Soleus muscle activity increased with an increase in speed in PD-affected individuals, particularly in severely affected individuals compared to the reference group. Discussion/Conclusion: The mechanism for increasing speed appears to differ between PD-affected individuals and physically fit individuals. Soleus excitation during stance may be a control parameter for walking speed that is disturbed in PD, although age is likely to be a confounding factor. Further research is needed to understand the mechanisms underpinning these positive responses to interactive treadmill training and its impact on community walking. Keywords: Parkinson's disease, Gait initiation, Gait Cycles, treadmill walking, speed change.Background: Parkinson's disease (PD) affects the ability of individuals to initiate movement and change muscle activity during gait initiation (GI) and during variations in walking speed. The present study aims to investigate the biomechanics parameters (kinetics and kinematics) and muscle activity characteristics during GI and variation in speed while walking on a treadmill and overground (OG) for PD-affected individuals and physically fit people. Methods: In this study, participants (n=17) included a physical fit (n= 11, aged 31.72 +/17.91 years) and a Parkinson’s (n= 6, aged 67.33 +/-11.57 years, disease duration 13.5 +/8.69). Both groups were evaluated while walking on the treadmill and over the ground for two phases. The first phase was Gait initiation, where the participants were asked to start walking at their comfortable speed for two gait cycles on the treadmill and OG. The second phase was speed variation, where the participants also walked at their comfortable speed, and increased their speed in response to visual instruction on screen. However, on the ground, they were asked to change their speed after their fifth walking step. A self-pacing treadmill synchronised with a virtual reality screen (MotekMedical, the Netherlands) and A 12-camera motion capture system (Vicon Motion Systems, UK) integrated with two embedded force plates and a wireless EMG system (Trigno, Delsys, USA) collected the biomechanical and muscle excitation data. Three gait cycles; before, during and immediately after the speed change was used for the analysis of the speed variation. Data were limited to lower limb joints and three muscles (tibialis anterior, gastrocnemius and soleus. Differences in the percentage of contraction and magnitude of muscle activation (area under the curve, AUC) were compared before and during the speed change. Results: PD-affected individuals spent less time on GI during treadmill walking (2.06 s ± 0.39) than the healthy reference group (2.25 s ± 0.42) but more time with OG walking (1.95s ±0.25) compared to the reference group (1.49s ±0.56). The reference group had a greater range of lower limb joint movement than the PD group during GI on both walking surfaces. The power produced at the hip and ankle joint by the reference group was higher than the overall PD group. The magnitude of muscle activation was lower in the PD group than the reference group, and the severity of the disease affected the magnitude of the muscle activation. At speed variation, both the reference and PD groups showed an increase in speed. Cadence declined in the reference group but elevated in the PD group. Soleus muscle activity increased with an increase in speed in PD-affected individuals, particularly in severely affected individuals compared to the reference group. Discussion/Conclusion: The mechanism for increasing speed appears to differ between PD-affected individuals and physically fit individuals. Soleus excitation during stance may be a control parameter for walking speed that is disturbed in PD, although age is likely to be a confounding factor. Further research is needed to understand the mechanisms underpinning these positive responses to interactive treadmill training and its impact on community walking. Keywords: Parkinson's disease, Gait initiation, Gait Cycles, treadmill walking, speed change

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

Peak Trailing Limb Angle and Propulsion Symmetry in Individuals with Below Knee Amputation

Background: Individuals with lower extremity amputation often present with kinematic and kinetic gait asymmetries and often have difficulty achieving symmetrical walking using their prescribed prosthesis. To understand the impact of limb loss on gait measures, studies often compare individuals with lower limb amputation to healthy control participants or compare the amputated limb to the uninvolved limb while completing a specified task like steady state walking. Commonly implemented treatments for individuals with lower limb amputation are based upon the assumption that equal use of both legs (symmetry) while completing bipedal tasks (e.g., walking) would be beneficial, matching the behavior seen in healthy control individuals. Underlying kinematic or kinetic symmetry, as well as a potential relationship of the two biomechanical gait variables in individuals with below knee amputation have not been thoroughly evaluated during steady state treadmill walking. Methods: We explored potential underlying (a)symmetries in peak trailing limb angle (kinematic) and peak anterior ground reaction force (kinetic) in individuals with below knee amputation walking at self-selected walking speed on a treadmill without upper extremity support. We then implemented real-time visual feedback to alter symmetry and examine the potential relationship between peak trailing limb angle and peak anterior ground reaction force. Later, we recruited and tested healthy control individuals with and without a solid ankle foot orthosis (SAFO) walking at their self-selected walking speed on a treadmill and exposed them to a similar visual feedback program to alter their baseline (a)symmetry. Population: We enrolled eleven of the planned twenty-four individuals with unilateral below knee amputation and fourteen healthy control participants without any lower extremity pathology or gait abnormality. Results: We found that individuals with below knee amputation do have peak trailing limb and anterior ground reaction force asymmetries and unencumbered healthy control individuals demonstrate symmetry of the same outcome measures while walking on a treadmill at self-selected walking speed. The use of real time visual feedback yielded statistically significant differences in peak trailing limb angle in healthy control participants without a solid ankle foot orthosis (p=0.04), peak and impulse anterior ground reaction forces when wearing a solid ankle foot orthosis (p=0.04). Statistically significant correlation between peak trailing limb angle and peak anterior ground reaction force were found in individuals with below knee amputation at baseline (p=0.0004), with real time visual feedback for peak trailing limb angle (p\u3c0.0001), and peak anterior ground reaction force (p=0.0002). Conclusions: Real time visual feedback is one intervention used to alter walking symmetry. Our results do not demonstrate an overwhelming response to real time visual feedback by individuals with below knee amputation or their healthy control counterparts and should be interpreted with caution. This work does provide meaningful information for further studies and interventions to alter symmetry during steady state walking and begins to explore the potential relationship between peak trailing limb angel and peak anterior ground reaction force production during self-selected treadmill walking in individuals with below knee amputation as well as otherwise healthy control individuals

Depression, Volition, and Death: The Effect of Depressive Disorders on the Autonomous Choice to Forgo Medical Treatment

Many contemporary models of medical ethics champion patient autonomy to counterbalance historically paternalistic decision-making processes. These models tend to suggest an autonomous agent free from cognitive bias and systematic distortion (e.g., Kantian or Cartesian rational agents). Evidence is emerging from the fields of cognitive psychology, cognitive science, and neuroscience that fundamentally challenge this cognitive model, demonstrating the dependence of cognition on deeper, avolitional structures (e.g., backstage cognition, cognitive heuristics and biases, automaticity, emotionally-valenced memory, etc.), and hence, shifting the cognitive model towards reductionistic and deterministic philosophies and psychologies. Medical ethics models must adapt their sense of autonomy in light of these findings if the term is to have any meaning - absent this necessary adaptation, medical ethics centers around a cognitive agent that does not actually exist. In contrast to the homuncular models championed (i.e., overly rationalistic and lacking an account of empirically-validated cognitive phenomena), a cognitive model of autonomy is proposed, along with useful psychometrics and a case metric to assist clinicians in assessing the possibility of compromised autonomy in patients electing to forgo medical treatment

Observing from the Margins: James Parkinson and the Shaking Palsy

Abstract In 1817, James Parkinson (1755-1824) published An Essay on the Shaking Palsy, describing paralysis agitans, or the shaking palsy, a condition he believed to be a specific and newly characterized disease. The disease concept specified both a constellation of signs and symptoms, including an abnormal gait, tremor, and difficulty initiating movement, and a specific order in which these signs and symptoms appeared, regardless of sufferers’ individual constitutions. Existing biographical and scholarly work about Parkinson and what is now known as Parkinson’s disease explicates the Essay but does not explore how Parkinson came to write it; his initial observations and subsequent conceptualizing of the disease have not been examined. Using the framework of the history of disease, this dissertation explores the early history of the shaking palsy, beginning with the training in observation that enabled Parkinson to envision the disease. He acquired this training in several settings: in his apprenticeship as a surgeon-apothecary and subsequent hospital experience; through his later period of study with John Hunter; and through his intensive study of fossils and chemistry. Next, it explores Parkinson’s neighborhood in Shoreditch, an increasingly impoverished suburb of London, where his medical work included attendance at madhouses and the parish workhouse. It then examines what inhabiting that environment would have allowed Parkinson to see. At a time when disease was increasingly seen as localized in the body’s tissues, correlatable with characteristic pathologic lesions visible at autopsy, the shaking palsy lacked a characteristic lesion to justify its classification as a new disease. To identify, bound, and define the disease, Parkinson needed a different conceptual framework to structure his ideas. This he accomplished using the framework of case histories and case series, a method he had employed in earlier published work. The shaking palsy continued to lack a pathologic explanation for many decades after Parkinson published the Essay. The dissertation ends by exploring how the disease concept survived and came into general use during the first decades following the Essay’s publication

Actas de SABI2020

Los temas salientes incluyen un marcapasos pulmonar que promete complementar y eventualmente sustituir la conocida ventilación mecánica por presión positiva (intubación), el análisis de la marchaespontánea sin costosos equipamientos, las imágenes infrarrojas y la predicción de la salud cardiovascular en temprana edad por medio de la biomecánica arterial