Analysis of Affective State as Covariate in Human Gait Identification

There is an increased interest in the need for a noninvasive and nonintrusive biometric identification and recognition system such as Automatic Gait Identification (AGI) due to the rise in crime rates in the US, physical assaults, and global terrorism in public places. AGI, a biometric system based on human gait, can recognize people from a distance and current literature shows that AGI has a 95.75% success rate in a closely controlled laboratory environment. Also, this success rate does not take into consideration the effect of covariate factors such as affective state (mood state); and literature shows that there is a lack of understanding of the effect of affective state on gait biometrics. The purpose of this study was to determine the percent success rate of AGI in an uncontrolled outdoor environment with affective state as the main variable. Affective state was measured using the Profile of Mood State (POMS) scales. Other covariate factors such as footwear or clothes were not considered in this study. The theoretical framework that grounded this study was Murray\u27s theory of total walking cycle. This study included the gait signature of 24 participants from a population of 62 individuals, sampled based on simple random sampling. This quantitative research used empirical methods and a Fourier Series Analysis. Results showed that AGI has a 75% percent success rate in an uncontrolled outdoor environment with affective state. This study contributes to social change by enhancing an understanding of the effect of affective state on gait biometrics for positive identification during and after a crime such as bank robbery when the use of facial identification from a surveillance camera is either not clear or not possible. This may also be used in other countries to detect suicide bombers from a distance

Patterned Plantar Stimulation During Gait

It is well established that the soles of the feet are involved and aid in balance control. However, it is not well understood the exact role that the feet play in gait control. During walking, the center of pressure (CoP) takes a predictable and repeated path along the plantar surfaces, going from heel to toe. This CoP has been established to be vital for postural control during standing, the plantar surfaces may perform a similar role during walking by perceiving this CoP path. Most studies use vibro-tactile stimulation on the plantar surfaces during the entire gait cycle, including the swing phase. However, no studies have investigated the effects of different patterns of sequential stimulation on the plantar surfaces during the stance phase of gait. Therefore, the following chapters describe a method of testing this effect, and demonstrating how such patterned plantar stimulation alters gait in healthy young adults. This method of testing was developed such that plantar stimulation would activate specifically during the stance phase of the gait cycle, and activate in a gait-like or an abnormal sequence. We then hypothesized that stimulation in an abnormal sequence would result in gait and balance deficits when compared to stimulation that followed the natural sequence during walking. Additionally, that walking on an inclined surface would increase the effects of the tactile stimulation sequences on such measures when compared with no stimulation. We tested a total of nine healthy adults and found very minimal effects from the stimulation in any pattern. This demonstrates that healthy adults have the ability to adjust and reweigh sensory information from the plantar surfaces such that gait and balance outcomes show minimal or no deficits when foot-sole tactile sensory sequences are manipulated during slow walking. Additionally, that the perception of the CoP movement may be predominately supplied by slow adapting fibers that are not typically sensitive to vibrations. This work gives indication to the flexibility and adaptability of a healthy motor control system and demonstrates a method of testing such a system with an online stimulation control software

A wearable biofeedback device to improve motor symptoms in Parkinson’s disease

Dissertação de mestrado em Engenharia BiomédicaThis dissertation presents the work done during the fifth year of the course Integrated Master’s in Biomedical Engineering, in Medical Electronics. This work was carried out in the Biomedical & Bioinspired Robotic Devices Lab (BiRD Lab) at the MicroElectroMechanics Center (CMEMS) established at the University of Minho. For validation purposes and data acquisition, it was developed a collaboration with the Clinical Academic Center (2CA), located at Braga Hospital. The knowledge acquired in the development of this master thesis is linked to the motor rehabilitation and assistance of abnormal gait caused by a neurological disease. Indeed, this dissertation has two main goals: (1) validate a wearable biofeedback system (WBS) used for Parkinson's disease patients (PD); and (2) develop a digital biomarker of PD based on kinematic-driven data acquired with the WBS. The first goal aims to study the effects of vibrotactile biofeedback to play an augmentative role to help PD patients mitigate gait-associated impairments, while the second goal seeks to bring a step advance in the use of front-end algorithms to develop a biomarker of PD based on inertial data acquired with wearable devices. Indeed, a WBS is intended to provide motor rehabilitation & assistance, but also to be used as a clinical decision support tool for the classification of the motor disability level. This system provides vibrotactile feedback to PD patients, so that they can integrate it into their normal physiological gait system, allowing them to overcome their gait difficulties related to the level/degree of the disease. The system is based on a user- centered design, considering the end-user driven, multitasking and less cognitive effort concepts. This manuscript presents all steps taken along this dissertation regarding: the literature review and respective critical analysis; implemented tech-based procedures; validation outcomes complemented with results discussion; and main conclusions and future challenges.Esta dissertação apresenta o trabalho realizado durante o quinto ano do curso Mestrado Integrado em Engenharia Biomédica, em Eletrónica Médica. Este trabalho foi realizado no Biomedical & Bioinspired Robotic Devices Lab (BiRD Lab) no MicroElectroMechanics Center (CMEMS) estabelecido na Universidade do Minho. Para efeitos de validação e aquisição de dados, foi desenvolvida uma colaboração com Clinical Academic Center (2CA), localizado no Hospital de Braga. Os conhecimentos adquiridos no desenvolvimento desta tese de mestrado estão ligados à reabilitação motora e assistência de marcha anormal causada por uma doença neurológica. De facto, esta dissertação tem dois objetivos principais: (1) validar um sistema de biofeedback vestível (WBS) utilizado por doentes com doença de Parkinson (DP); e (2) desenvolver um biomarcador digital de PD baseado em dados cinemáticos adquiridos com o WBS. O primeiro objetivo visa o estudo dos efeitos do biofeedback vibrotáctil para desempenhar um papel de reforço para ajudar os pacientes com PD a mitigar as deficiências associadas à marcha, enquanto o segundo objetivo procura trazer um avanço na utilização de algoritmos front-end para biomarcar PD baseado em dados inerciais adquiridos com o dispositivos vestível. De facto, a partir de um WBS pretende-se fornecer reabilitação motora e assistência, mas também utilizá-lo como ferramenta de apoio à decisão clínica para a classificação do nível de deficiência motora. Este sistema fornece feedback vibrotáctil aos pacientes com PD, para que possam integrá-lo no seu sistema de marcha fisiológica normal, permitindo-lhes ultrapassar as suas dificuldades de marcha relacionadas com o nível/grau da doença. O sistema baseia-se numa conceção centrada no utilizador, considerando o utilizador final, multitarefas e conceitos de esforço menos cognitivo. Portanto, este manuscrito apresenta todos os passos dados ao longo desta dissertação relativamente a: revisão da literatura e respetiva análise crítica; procedimentos de base tecnológica implementados; resultados de validação complementados com discussão de resultados; e principais conclusões e desafios futuros

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

The utility of gait as a biological characteristic in forensic investigations – An empirical examination of movement pattern variation using biomechanical and anthropological principles

Forensic gait analysis is generally defined as the analysis of gait features from video footage to assist in criminal investigations. Although an attractive means to detect suspects since data can be collected from a distance without their knowledge, forensic gait analysis presently lacks method validation and quality standards, not only due to insufficient research, but also because certain scientific foundations, such as the assumption of gait uniqueness, have not been adequately addressed. To test the scientific basis of this premise, a suitable dataset replicating an ideal forensic gait analysis scenario was compiled from the Karlsruhe Institute of Technology (Germany) database. Biomechanical analysis of sagittal plane human motion in the bilateral shoulder, elbow, hip, knee, and ankle joints was conducted across complete gait cycles of twenty participants, to investigate the degree to which intraindividual variation impacts interindividual variation, according to the following aims: (1) to better understand the relationship between form (anatomy) and function (physiology) of human gait, (2) to investigate the basis of gait uniqueness by examining similarities and differences in joint angles, and (3) to build upon current theoretical foundations of gait-based human identification. The findings indicate different degrees of movement asymmetry given body region and gait sub-phase, thereby challenging previous methods employing interchangeable use of bilateral motion data, and the use of ‘average’ gait cycles to represent the gait of an individual irrespective of body side. Furthermore, interindividual variability in all five joints is influenced by body side to different extents depending on gait sub-phase and body region, thereby challenging the claim of holistic uniqueness of gait features across all body regions and gait events. Given the findings of this thesis and paucity regarding empirical basis to support expertise, exerting caution when evaluating gait-based evidence admissibility is highly recommended, since the utility of gait in identification is currently limited

Intelligent Biosignal Processing in Wearable and Implantable Sensors

This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brain–machine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine

Development and Implementation of Mathematical Modeling, Vibration and Acoustic Emission Technique to Correlate \u3cem\u3eIn Vivo\u3c/em\u3e Kinematics, Kinetics and Sound in Total Hip Arthroplasty with Different Bearing Surfaces

The evaluation of Total Hip Arthroplasty (THA) outcome is difficult and invasive methods are often applied. Fluoroscopy has been used as an in vivo diagnostic technique to determine separation which may lead to vibration propagation and audible interactions. The objective of this study was to develop a new, non-invasive technique of digitally capturing vibration and sound emissions at the hip joint interface and to correlate those with the hip kinematics derived from fluoroscopy. Additionally, an examination of the role of hip mechanics on walking performance in THA subjects of various bearings surfaces was performed. In vivo kinematics, kinetics, corresponding vibration and sound measurements of THA were analyzed post-operatively using video-fluoroscopy, mathematical modeling, sound sensors and accelerometers during gait on a treadmill. Twenty-seven subjects (31 hips) with a metal-on-metal, metal-on-polyethylene, ceramic-on-ceramic, ceramicon- polyethylene or metal-on-metal polyethylene-sandwich THA were analyzed. A data acquisition system was used to amplify the signal and filter out associated frequencies attributed to noise. The sound measurements were correlated to in vivo kinematics. A mathematical model of the human extremity was derived to determine in vivo bearing and soft-tissue forces. For all bearings a distinct correlation of a high frequency sound occurring at the time when the femoral head slides back into the acetabular component was observed. Subjects having a hard-on-hard bearing seemed to attenuate a squeaking and/or impacting sound, while those having polyethylene liner only revealed a knocking sound attributed to impact loading conditions. For the first time, audible effects can be derived in vivo and the examined correlation brings valuable insight into the hip joint performance in an inexpensive and non-invasive manner. This research may allow for a further correlation to be derived between sound and different types of failure mechanisms. Results from this study will give surgeons and engineers a better understanding of in vivo mechanics of the hip joint and this way improve the quality of life of THA patients. In addition, the developed technique builds the first milestone in the design and implementation of a cost effective, non-invasive diagnostic technique which has the potential to become a routine diagnosis of joint conditions

WALKING FOR OBJECT TRANSPORT: AN EXAMINATION OF THE COORDINATIVE ADAPTATIONS TO LOCOMOTOR, PERCEPTUAL, AND MANUAL TASK CONSTRAINTS

The goal of this dissertation was to understand how the intrinsic dynamics of gait adapt to support the performance of an ecologically relevant object transport task. A common object transport task is walking with a cup of water. Because the water can move relatively independent of the cup, the cup and water system is classified as a complex object. To model this task participants carried a cup with a wooden lid placed on top. On the lid there was a circular region with the same circumference as the cup and a ball. The object of the task was to keep the ball inside the circular region. We explored two questions: 1) how do the intrinsic coordinative gait dynamics adapt to support object transport during walking? And 2) how do individuals adapt to manually control a complex object when asked to concurrently attend to visual information? To address question 1, participants walked on a treadmill at six speeds (0.4 - 1.4 m/s) and performed three conditions: normal walking, walking with a cup only (Cup), and walking with the cup and ball (Cup-Ball). When performing the Cup-Ball condition, as gait speed increased, pelvis-thorax coordination was more in-phase compared to the normal walking and the Cup conditions. Arm-leg coordination was affected by the performance of the Cup-Ball condition. On the constrained side arm-leg coordination was 2:1 while a 1:1 relationship was maintained on the unconstrained side. A correlation between the amplitude of the unconstrained arm and manual task performance revealed a significant negative correlation as gait speed increased, indicating that individuals who reduced their arm swing performed better. To address question 2, participants walked on a treadmill at three gait speeds under four task conditions: normal walking, walking with the cup and ball system (Cup-Ball), walking while identifying visual stimuli (Visual), and a combined condition where participants walked with the cup and ball system while identifying visual stimuli (Cup-Ball-Vis). The addition of the visual task in study 2 resulted in the head orientation to be more extended relative to the trunk with a larger range of motion compared to the manual task only condition; participants optimized on the visual task at the expense of manual task performance. In both manual task conditions pelvis-thorax coordination was more in-phase as gait speed increased and more variable compared to the walking only condition. The latter result demonstrates the functionality of increased coordination variability during object transport tasks. The amplitude of the unconstrained arm decreased as the system became more constrained (i.e., going from walking only to Cup-Ball to Cup-Ball-Vis tasks). Although the arm amplitude decreased, the unconstrained arm maintained a 1:1 arm-leg coordination while the constrained arm was in a 2:1 relationship for both manual task conditions. This result demonstrates that the unconstrained arm continues to move to counteract angular momentum imparted by the legs while the arm carrying the object is coupled to the step frequency, counteracting disturbances imposed by heel contacts. The overall results from both studies demonstrate that the body’s natural walking dynamics adapt to support manual task performance. The segments not directly involved in the task continue to interact to maintain intrinsic gait dynamics. This dissertation makes significant contributions to the literature by demonstrating: 1) asymmetries in arm-leg coordination are exploited by the body to maintain manual task performance and intrinsic gait dynamics; 2) amplitude of the freely swinging arm is an important factor in task performance during object transport; and 3) increased variability at the level of the pelvis-thorax interaction plays a functional role in maintaining both manual and visual task performance. The significance of the findings here is that they demonstrate how task constraints alter intrinsic coordination dynamics during walking in order to support performance while at the same time maintaining gait stabilit