Wearable Systems Based Gait Monitoring And Analysis

Wearable Systems Based Gait Monitoring and Analysis provides a thorough overview of wearable gait monitoring techniques and their use in health analysis. The text starts with an examination of the relationship between the human body’s physical condition and gait, and then introduces and explains nine mainstream sensing mechanisms, including piezoresistive, resistive, capacitive, piezoelectric, inductive, optical, air pressure, EMG and IMU-based architectures. Gait sensor design considerations in terms of geometry and deployment are also introduced. Diverse processing algorithms for manipulating sensors outputs to transform raw data to understandable gait features are discussed. Furthermore, gait analysis-based health monitoring demonstrations are given at the end of this book, including both medical and occupational applications. The book will enable students of biomedical engineering, electrical engineering, signal processing, and ergonomics and practitioners to understand the medical and occupational applications of engineering-based gait analysis and falling injury prevention methods.

Continuous lower body monitoring is an important step for real-time feedback training of runners and in-home rehabilitation assessment. Optical motion capture systems are the gold standards for gait analysis, but they are spatially limited to laboratories. Recently, wearable sensors have gained attention as unobtrusive methods to analyze gait metrics and health conditions. In this study, a wearable system capable of estimating lower body joint angles in sagittal, frontal, and transverse planes during gait was developed. A prototype with fiber strain sensors was fabricated. The positions of the sensors on the pelvis were optimized using a genetic algorithm. A cohort of ten people completed 15 minutes of running at 5 different speeds for gait analysis by our prototype device. The joint angles were estimated by a deep convolutional neural network in inter- and intra-participant scenarios. In intra-participant tests, root mean squared error (RMSE) and normalized root mean squared error (NRMSE) of less than 2.2° and 5.3 %, respectively, were obtained for hip, knee, and ankle joints in sagittal, frontal, and transverse planes. The RMSE and NRMSE in inter-participant tests were less than 6.4° and 10%, respectively, in the sagittal plane. The accuracy of this device and methodology could yield potential applications as a soft wearable device for gait monitoring.

Footwear based wearable sensors are used in applications such as activity monitoring, gait analysis, post-stroke rehabilitation, body weight measurements, and energy expenditure estimation. Such wearable sensors typically required the modification or alteration of the shoe, which is not typically feasible for large populations without the direct involvement of shoe manufacturers. This dissertation presents an insole-based wearable sensor (SmartStep) that has its electronics fully embedded into a generic insole, which can be used with a large variety of shoes and, thus, resolves the need for shoe modification. The SmartStep is an always-on electronic device that comprises of inertial sensors and resistive pressure sensors implemented around a system on chip with Bluetooth low energy (BLE) connectivity. The dissertation explains a novel Android application methodology to interface multiple BLE sensors. As a part of the research, SmartStep's predecessor, SmartShoe, was tested in an application scenario of gait monitoring of children with cerebral palsy. Novel signal processing algorithms were developed to deal with the effect of orthotics on pressure sensors. Machine learning models were used to recognize 3 major activities (sitting, standing and walking) with greater than 95% accuracy. The gait parameter estimation resulted in average error less than 6% across a range of temporal gait parameters. The SmartStep device was utilized in a study for recognizing activities of daily living (ADL) in adults. An upper-body, wrist-worn sensor was also utilized in the same study to compare the effectiveness of upper and lower body-worn sensors in recognizing ADL. The indirect calorimetry data from a portable metabolic system (Cosmed K4b), collected in the same study, were used to develop energy expenditure (EE) estimation models. Two different sets of steady state activity branched models were developed, along with models for transition activities. The EE models were validated on the data from a room calorimeter. SmartStep was 90% accurate in recognizing a broad set of nine ADLs, including household activities; while having 6% validation error in estimating total energy expenditure. These results suggest that SmartStep is accurate in recognizing multiple activities of daily living and in energy expenditure estimation.

As diverse as tomorrow’s society constituent groups may be, they will share the common requirements that their life should become safer and healthier, offering higher levels of effectiveness, communication and personal freedom. The key common part to all potential solutions fulfilling these requirements is wearable embedded systems, with longer periods of autonomy, offering wider functionality, more communication possibilities and increased computational power. As electronic and information systems on the human body, their role is to collect relevant physiological information, and to interface between humans and local and/or global information systems. Within this context, there is an increasing need for applications in diverse fields, from health to rescue to sport and even remote activities in space, to have real-time access to vital signs and other behavioral parameters for personalized healthcare, rescue operation planning, etc. This book’s coverage will span all scientific and technological areas that define wearable monitoring systems, including sensors, signal processing, energy, system integration, communications, and user interfaces. Six case studies will be used to illustrate the principles and practices introduced.

Wearable Sensors: Fundamentals, Implementation and Applications has been written by a collection of experts in their field, who each provide you with an understanding of how to design and work with wearable sensors. Together these insights provide the first single source of information on wearable sensors that would be a fantastic addition to the library of any engineers working in this field. Wearable Sensors covers a wide variety of topics associated with development and applications of wearable sensors. It also provides an overview and a coherent summary of many aspects of wearable sensor technology. Both professionals in industries and academic researchers need this package of information in order to learn the overview and each specific technology at the same time. This book includes the most current knowledge on the advancement of light-weight hardware, energy harvesting, signal processing, and wireless communications and networks. Practical problems with smart fabrics, biomonitoring and health informatics are all addressed, plus end user centric design, ethical and safety issues. The new edition is completely reviewed by key figures in the field, who offer authoritative and comprehensive information on the various topics. A new feature for the second edition is the incorporation of key background information on topics to allow the less advanced user access to the field and to make the title more of an auto-didactic book for undergraduates. Provides a full revision of the first edition, providing a comprehensive and up-to-date resource of all currently used wearable devices in an accessible and structured manner Helps engineers manufacture wearable devices with information on current technologies, with a focus on end user needs and recycling requirements This book provides a fully updated overview of the many aspects of wearable sensor technology in one single volume, enabling engineers and researchers to fully comprehend the field and to identify opportunities

Provides a detailed clinical introduction to the application of biomechanics to the understanding and treatment of walking disorders. Practical issues in the performance of a three-dimensional clinical gait analysis are covered, together with several clinical cases illustrating the interpretation of findings. These cases also demonstrate the use of a variety of treatment methodologies, including physical therapy, walking aids, prosthetics and orthotics, botulinum toxin and surgery.

This book is a printed edition of the Special Issue "Wearable Electronics and Embedded Computing Systems for Biomedical Applications" that was published in Electronics

Abnormalities and irregularities in walking (gait) are predictors and indicators of bothdisease and injury. Gait has traditionally been monitored and analyzed in clinical settings using complex video (camera-based) systems, pressure mats, or a combination thereof. Wearable gait sensors offer the opportunity to collect data in natural settings and to complement data collected in clinical settings, thereby offering the potential to improve quality of care and diagnosis for those whose gait varies from healthy patterns of movement. This paper presents a gait monitoring system designed to be worn on the inner knee or upper thigh. It consists of low-power Hall-effect sensors positioned on one leg and a compact magnet positioned on the opposite leg. Wireless data collected from the sensor system were used to analyze stride width, stride width variability, cadence, and cadence variability for four different individuals engaged in normal gait, two types of abnormal gait, and two types of irregular gait. Using leg gap variability as a proxy for stride width variability, 81% of abnormal or irregular strides were accurately identified as different from normal stride. Cadence was surprisingly 100% accurate in identifying strides which strayed from normal, but variability in cadence provided no useful information. This highly sensitive, non-contact Hall-effect sensing method for gait monitoring offers the possibility for detecting visually imperceptible gait variability in natural settings. These nuanced changes in gait are valuable for predicting early stages of disease and also for indicating progress in recovering from injury.

This book consists of papers describing developments and trends all over the world in the areas of smart wearable monitoring and diagnostic systems, smart treatment systems, biomedical clothing and smart fibres and fabrics.