Preservation and Reproduction of Human Motion Based on a Motion-Copying System

In this chapter, a novel method for preserving and reproducing human motion based on haptic technology is described. Haptic technology makes it possible to preserve and reproduce human motion using a paired master and slave system. Because it is possible to preserve motion information based on position trajectory and force input, future human support technology that will facilitate skill acquisition, physical rehabilitation will be developed and will facilitate personal adaptation, tele-communication, et cetera. Once human motions are preserved, it will be possible to process them for various applications. For example, being able to reproduce the speed and trajectory of motion will allow for adjustments that fit the desired function. As a result, the temporal and spatial coupling of perception and action can be attained. This type of physical extension technology based on haptics will be important for the future of human support in society.

Nursing in Integrative Medicine and Nurses’ Engagement in Caring-Healing

In 2008, the authors’ team started an ongoing project to administer music therapy sessions for patients with neurodegenerative diseases. Studies were made conducted from the “caring” perspective to evaluate the effects of music therapy on the mental health of the patients (Inomata, 2008a, Inomata 2008b) and on the role of nurses in integrative medicine (Inomata, 2008c). On the basis of the findings from these studies, music therapy programs were designed and conducted to meet the different needs of various neurodegenerative diseases. This project was the first ever reported music therapy initiative undertaken as a multi-disciplinary collaborative work and in partnership with a patients’ group (Saji, 2010). The findings from four years of running the project are summarized as follows: (1) Music therapy helped maintain/improve the QOL(Quality of Life) level of neurodegenerative disease patients, which would otherwise deteriorate with the progress of symptoms; (2) There was an improvement in the patients’ psychological and spiritual health as exemplified by the expansion of consciousness and rebuilding of relationships; (3) The project increased the feeling of partnership among the multi-disciplinary team members; (4) Care providers shared values such as self-belief and respect for both the self and others; (5) Caring for patients’ emotional side by being compassionate and staying with them and/or listening to them resulted in a stronger care provider-patient bond; (6) Nurses were engaged in the building a healing environment as “healers,” and the patients found more hope in everyday life.

Functional Electrical Stimulation (FES) Control for Restoration and Rehabilitation of Motor Function

Functional electrical stimulation (FES) has been studied and clinically applied to restoring or assisting motor functions lost due to spinal cord injury or cerebrovascular disease. Electrical stimulation without control of functional movements is also used for therapy or in rehabilitation training. In recent years, one of the main focuses of FES studies has been its application for rehabilitation of motor function. In this review, the authors first present the basics of applying electrical stimulation to the neuromuscular system for motor control. Then, two methods of FES control are discussed: controllers for FES based on feedback error learning (FEL) and on cycle-to-cycle control of limb movements. The FEL-FES controller can be practical in FES applications that need to control the musculoskeletal system that involves various nonlinear characteristics and delay in its responses to electrical stimulation. The cycle-to-cycle control is expected to be effective in controlling repetitive movements for rehabilitation training. Finally, a study on ankle dorsiflexion control during the swing phase using an integrated system of FES control and motion measurement with wearable sensors for rehabilitation is presented.

Molecular Network Analysis of Target RNAs and Interacting Proteins of TDP-43, a Causative Gene for the Neurodegenerative Diseases ALS/FTLD

TAR DNA-binding protein-43 (TDP-43) is an evolutionarily conserved nuclear protein that regulates gene expression by forming a multimolecular complex with a wide variety of target RNAs and interacting proteins. Abnormally phosphorylated, ubiquitinated, and aggregated TDP-43 proteins constitute a principal component of neuronal and glial cytoplasmic and nuclear inclusions in the brains of patients with amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), establishing a novel clinical entity designated TDP-43 proteinopathy. Although increasing evidence suggests that the neurodegenerative process underlying ALS and FTLD is attributable to a toxic gain of function or a loss of cellular function of TDP-43, the precise molecular mechanisms remain largely unknown. Recent advances in systems biology enable us to characterize the global molecular network extracted from large-scale data of the genome, transcriptome, and proteome with the pathway analysis tools of bioinformatics endowed with a comprehensive knowledge base. The present study was conducted to characterize the comprehensive molecular network of TDP-43 target RNAs and interacting proteins, recently identified by deep sequencing with next-generation sequencers and mass spectrometric analysis. The results propose the systems biological view that TDP-43 serves as a molecular coordinator of the RNA-dependent regulation of gene transcription and translation pivotal for performing diverse neuronal functions and that the disruption of TDP-43-mediated molecular coordination induces neurodegeneration in ALS and FTLD.

Fusion Physiological Sensing System for Healthcare

In the super-aging society, daily healthcare monitoring has become increasingly emphasized as a possible approach for the early diagnosis and timely treatment of lifestyle-related diseases. A wide variety of information transfers and platforms have been developed for daily healthcare monitoring. Using these techniques, the commercially available devices for home healthcare are also networked. However, techniques for obtaining physiological information are unfocused, and in such a case, even useful data cannot be obtained even if the network system is applied. Given these considerations, the authors have investigated a new network system combined with new bioinstrumentation techniques, i.e., the fusion physiological sensing system and its applicability for the daily healthcare monitoring. In particular, as contributions towards the development of healthcare technology, two promising monitoring techniques, ambulatory and non-conscious physiological monitoring, have been developed. These methods can contribute to the fields of the personal healthcare, medical care, and rehabilitation through their fusion with information and communications technology. The utility of these systems are reported according to the results of practical use, in addition to the outline of the sensing techniques in this chapter.

A Neuromorphic Robot Vision System to Predict the Response of Visual Neurons

The author of this chapter describes a binocular robotic vision system that was designed to emulate the neural images of cortical cells under vergence eye movements. The robotic vision system is constructed by employing a combinational strategy of neuromorphic engineering and conventional digital technology. The system consists of two silicon retinas and a field programmable gate array (FPGA). The silicon retinas carry out Laplacian-Gaussian-like spatial filtering, mimicking the response properties of the vertebrate retina. The outputs of the silicon retina chips on the left and right cameras are transmitted to the FPGA. The FPGA receives the outputs from the two simple cell chips and calculates the responses of complex cells based on the disparity energy model. This system provides complex cell outputs tuned to five different disparities in real-time. The vergence control signal is obtained by pooling these multiple complex cell responses. The system is useful for predicting the neural images of the complex cells and for evaluating the functional roles of cortical cells in real situations.

Design of and Experimentation with a Walking Assistance Robot

To help patients with lower limb disabilities walk, a robot was designed to help train patients to stand up. An experimental prototype was developed, and experiments to train patients stand up and walk were performed using this robot. The results show that the robot can help patients to stand from a sitting position, which is the purpose of standing-up training. At the same time, the standing-up mechanism can coordinate with the walking assistance mechanism in the walking training mode, allowing the robot to help patients to perform rehabilitation walking training. The justification of the mechanism design was demonstrated, and thus, the robot can be used for stranding-up training and walking training.

A New, Non-Invasive in vivo Optical Blood Glucose Measurement Technique Using Near-Infrared Radiation (“Pulse Glucometry”) and a Proposal for “Pulse Hemo-Photometry” Blood Constituent Measurements

A recently proposed optical method for a non-invasive in vivo blood glucose level (BGL) measurement named “pulse glucometry” is introduced. This method is based on near-infrared living body spectroscopy to accurately obtain blood information. The remarkable feature of the method is the measurement of both the total transmitted radiation spectra in wavelength ? (I?) and the cardiac-related pulsatile component (?I?). When ?I? is superimposed on I?, the differential optical density (?OD?), which includes only arterial blood information, is obtained, thus avoiding interference from living tissues other than arterial blood. Another feature is the ability to measure the differential optical density (?OD?) in multiple wavelengths to avoid interference from blood constituents other than the target blood chemical (glucose). To support this methodology, a very fast near-infrared spectroscopic system was developed to obtain a photoplethysmographic cardiac signal with a resolution of 8 nm over a wavelength range of 900 to 1700 nm at a 100 Hz sampling frequency. An example of an in vivo BGL measurement is shown and indicates good prediction capabilities. This method can be expanded to the measurement of other blood constituents.

Description of and Applications for a Motion Analysis Method for Upper Limbs

In daily life, we often perform activities with the upper limbs. Various motions of the upper limbs are required when performing activities of daily living (ADL), such as eating, dressing, grooming, or operating a home appliance. When problems first occur with human upper limb motions, a detailed analysis should be performed to determine where the difficulty with motion exists and to identify conditions under which we can perform these activities more easily and efficiently. Next, adjustments should be made to the activity or to the interface design of appliances to reduce the difficulty posed by the problematic motion. In this chapter, the methods of motion analysis for human upper limbs are explained and the effective method of utilization is shown. A case study is also provided to demonstrate the analysis of the pointer operation for cerebral palsy patients using a laptop PC which operates by a graphical user interface operating system (GUI OS) to provide a barrier-free approach. Additionally, an applied case study of the motion analysis methods for human upper limbs is shown, and the countermeasure to develop an effective pointer operation for cerebral palsy patients is discussed.

Computational Study of the Hemodynamics of Cerebral Aneurysm Initiation

This chapter aims to present the authors’ recent findings from studies on the computational biomechanics of blood flow in human arteries and its application to the hemodynamics of cerebral aneurysm initiation. They first briefly outline the techniques of computational fluid dynamics used in blood flow simulations of anatomically realistic artery models reconstructed from medical images acquired with CT or MRI. Then, the time course of the blood flow velocity field in the medical image-based model of a human internal carotid artery (ICA) is shown as a result of a pulsatile blood flow simulation with CFD techniques. Finally, the chapter presents an overview of the concept of a novel hemodynamic indicator for cerebral aneurysm initiation, the gradient oscillatory number (GON). The distribution of the GON for the medical image-based ICA model is also demonstrated.