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We introduce an innovative wristband wireless device based on a dual wavelength NDIR optical measurement and an optimized thermo-fluidic channel to improve the extraction of the carbon dioxide gas from the blood within the heated skin region. We describe a signal processing model combining an innovative linear quadratic model of the optical measurement and a fluidic model. The evaluation is achieved using a cardiopulmonary exercise test (CPET). We compare carbon dioxide tension measurement at the forearm level using our device, with an electrochemical measurement at the forearm level, and an optical measurement of the end-tidal exhaled breath. These curves demonstrate a significant reduction of the variability of carbon dioxide pressure measurement with respect to the pressure dynamic range during the test.

Amid trends toward aging populations in developed nations, the number of people requiring nursing care has increased markedly. Slips and falls during ordinary daily activities are a common cause of fractured bones and muscle injury. Several studies have analyzed the movements produced by artificially generated slip and fall stimuli, but few have investigated these stimuli. We analyzed lower-limb motion following a slip and fall stimulus produced using a pulled free-walking system consisting of a controllable split-belt treadmill, where a speed difference between the belts could be applied to produce a slipping motion. In three male participants, we established slip motion by applying acceleration in the sagittal plane direction of the right leg immediately upon contact with the treadmill. Each participant demonstrated a different recovery method from falling.

While devices which allow scientists to perturb normal walking are becoming increasingly common, postural adaptations to these perturbations have not been fully quantified. One way to quantify postural responses to perturbations are through the assessment of variability of step length and width. In the present study we determined variability of both step length and width while subjects walked under perturbations of varying amplitude in roll, pitch, yaw, anteroposterior, lateral, and combined roll, pitch, yaw directions. Step kinematics were quantified using motion analysis. The majority of changes in step length variability occurred in Pitch (p<;0.01), mediolateral (p<;0.05) and anteroposterior (p<;0.01) directions. Changes in step width variability were most apparent in combined Roll-Pitch-Yaw (p<;0.01) as well as Roll (p<;0.05), and Yaw (p<;0.05) directions. These data demonstrate that sinusoidal perturbations while walking on a treadmill are sufficient to disrupt normal postural control. These conditions therefore may be useful in constructing rehabilitation programs to improve dynamic balance.

This paper presents a home-based Senior Fitness Test (SFT) measurement system by using an inertial sensor and a depth camera in a collaborative way. The depth camera is used to monitor the correct pose of a subject for a fitness test and any deviation from the correct pose while the inertial sensor is used to measure the number of a fitness test action performed by the subject within the time duration specified by the fitness protocol. The results indicate that this collaborative approach leads to high success rates in providing the SFT measurements under realistic conditions.

Accurate, non-intrusive and straightforward techniques for gait quality analysis can provide important information concerning the fall risk of a person. For this purpose an algorithm was developed which can measure step length and step time using the Kinect depth image. The validity of the measured step length and time is determined using the GAITRite walkway as a ground truth. The results of this validation confirm that the Kinect is well-suited for determining general parameters of a walking sequence (a Spearmans Correlation Coefficient (SCC) of 0.94 for average step length and 0.75 for average step time per walk), but we furthermore show that determining accurate results for single steps is more difficult (SCC of 0.74 for step length and 0.43 for step time for each step), making it harder to measure more complex gait parameters such as e.g. gait symmetry.

This study investigates ECG features, focusing on T-wave amplitude, from a wearable ECG device as a potential method for fitness monitoring in exercise rehabilitation. An automatic T-peak detection algorithm is presented that uses local baseline detection to overcome baseline drift without the need for preprocessing, and offers adequate performance on data recorded in noisy environments. The algorithm is applied to 24 hour data recordings from two subject groups with different physical activity histories. Results indicate that, while mean heart rate (HR) differs most significantly between the groups, T-amplitude features could be useful depending on the disparities in fitness level, and require further investigation on an individual basis.

The gait movement is a complex and essential process of the human activity. Yet, many types of diseases (neurological, muscular, orthopedic, etc.) can be diagnosed from the gait analysis. This paper introduces a novel method to quickly visualize the different body parts related to an (temporally shift-invariant) asymmetric movement in the human gait of a patient for daily clinical usage. The goal is to provide a cheap and easy-to-use method that measures the gait asymmetry and display results in a perceptual and intuitive way. This method relies on an affordable consumer depth sensor, the Kinect, which is very suitable for small room and fast diagnostic, since it is easy to setup and marker-less.

Locomotor training using treadmill has been shown to elicit significant improvements in locomotor ability for some children with cerebral palsy (CP), the functional gains are relatively small and it requires greater involvement from a physical therapist. Current robotic gait training systems are effective in reducing the strenuous work of a physical therapist during locomotor training, but are less effective in improving locomotor function in some children with CP due to the limitations of the systems. Thus, a 3D cable-driven robotic gait training system was developed and tested in five children with CP through a 6 week of long-term gait training. Results indicated that both overground walking speed and 6 minute walking distance improved after robot assisted treadmill training through the cable-driven robotic system, and partially retained at 8 weeks after the end of training. Results from this pilot study indicated that it seems feasible to conduct locomotor training in children with CP through the 3D cable-driven robotic system.

A self-paced treadmill that can simulate overground walking has the potential to improve the effectiveness of treadmill training for gait rehabilitation. We have implemented a self-paced treadmill without the need for expensive equipment such as a motion capture system and an instrumented treadmill. For this, an inexpensive depth sensor, ASUS XtionTM, substitutes for the motion capture system, and a low-cost commercial treadmill is considered as the platform of the self-paced treadmill. The proposed self-paced treadmill is also convenient because the depth sensor does not require markers placed on user's body. Through pilot tests with two healthy subjects, it is quantitatively and qualitatively verified that the proposed self-paced treadmill achieves similar performance as one which utilizes a commercial motion capture system (VICON) as well as an instrumented treadmill.

The present study assessed whether an unperceivable, noise-like electrical stimulation of a knee joint enhances the stability of quiet bipedal stance and treadmill walking in young subjects. The results showed that the slow postural sway measures in quiet bipedal stance were significantly reduced by the electrical noise (P<0.05). In the treadmill walking, low frequency component (below 1 Hz) of mediolateral acceleration, measured at the third lumbar vertebra, significantly decreased with the electrical noise (P<0.05), while there were no changes in the anteroposterior and vertical directions. These results indicate that the electrical noise to a knee joint can be applied to enhance postural control in quiet bipedal stance and treadmill walking.

The dynamic human body communication (HBC) propagation channel at 45 MHz was statistical characterized in this paper. A large amount of measurement data has been gathered in practical environment with real activities -treadmill running at different speeds in a lab room. The received power between two lower legs was acquired from three volunteers, with more than 60,000 snap shot of data in total. The statistical analyses confirmed that the HBC propagation channel at 45 MHz followed the Gamma and Lognormal distributions at the slower (2 km/h and 4 km/h) and faster (6 km/h and 8 km/h) running activities, respectively. The channel is insensitive to body motion with the maximum average fade duration is 0.0413 s and the most averaging bad channel duration time being less than 60 ms with the percentage of the bad channel duration time being less than 4.35%.

A new technology called estimated continuous cardiac output (esCCO) uses pulse wave transit time (PWTT) obtained from an electrocardiogram and pulse oximeter to measure cardiac output (CO) non-invasively and continuously. This study was performed to evaluate the accuracy of esCCO during exercise testing. We compared esCCO with CO measured by the echo Doppler aortic velocity-time integral (VTIao&#95;CO). The correlation coefficient between esCCO and VTIao&#95;CO was r= 0.87 (n= 72). Bias and precision were 0.33 ± 0.95 L/min and percentage error was 31%. The esCCO could detect change in VTIao&#95;CO larger than 1 L/min with a concordance rate of 88%. In polar plot, 83% of data are within 0.5 L/min, and 100% of data are within 1 L/min. Those results show the acceptable accuracy and trend ability of esCCO. Change in pre-ejection period (PEP) measured by using M-mode of Diagnostic Ultrasound System accounted for approximately half of change in PWTT. This indicates that PEP included in PWTT has an impact on the accuracy of esCCO measurement. In this study, the validity of esCCO during exercise testing was assessed and shown to be acceptable. The result of this study suggests that we can expand its application.

The goal of this study is to compare the effect of training by the University of Utah's Treadport versus a conventional treadmill on gait improvement of spinal-cord-injury (SCI) patients. Four incomplete SCI subjects who had reached a rehabilitation plateau were selected to have training first on the treadmill and then the Treadport. Spatiotemporal and gait parameters were utilized to make a comparison between the two training conditions. Overall, the results demonstrated statically significant improvements in most of the spatiotemporal as well as some of the gait parameters during training with the Treadport relative to the traditional treadmill.

Walking is the most common activity among people who are physically active. Standard practice physical activity characterization from body-mounted inertial sensors uses accelerometer-generated counts. There are two problems with this - imprecison (due to usage of proprietary counts) and incompleteness (due to incomplete description of motion). We address both these problems by directly predicting energy expenditure during steady-state treadmill walking from a hip-mounted inertial sensor comprised of a tri-axial accelerometer and a tri-axial gyroscope. We use Bayesian Linear Regression to predict energy expenditure based on modelling joint probabilities of streaming data. The prediction is significantly better with data from a 6 axis sensor as compared with streaming data from only 2 linear accelerations as is common in current practice. We also show how counts from a commercially available accelerometer can be reproduced from raw streaming acceleration data (up to a linear transformation) with high correlation (.9787 ± .0089 for the X-axis and .9141 ± .0460 for the Y-axis acceleration streams). The paper emphasizes the role of probabilistic techniques in conjunction with joint modeling of tri-axial accelerations and rotational rates to improve energy expenditure prediction for steady-state treadmill walking.

CardioBip (CB) is a hand-held patient-activated device for recording and wireless transmission of reconstructed 12-lead ECG (12CB) based on patient specific matrices. It has 5 contact points: 3 precordial and 2 on the device top serving as limb leads when touched by index fingers. To determine whether CB could be used to monitor coronary disease (CAD) patients, we compared 12CB to simultaneous 12-lead ECGs (12L) in patients with CAD, pre-and post-exercise treadmill testing (ETT). The study goals were to assess: (1) whether 12CB can accurately reconstruct and wirelessly transmit 12-lead ECGs in CAD patients during ETT recovery; (2) whether 12CB can be used to evaluate ST segment changes in patients with exercise-induced ischemia.

Walking impairments are a common sequela of neurological injury, severely affecting the quality of life of both adults and children. Gait therapy is the traditional approach to ameliorate the problem by re-training the nervous system and there have been some attempts to mechanize such approach. In this paper, we present a novel device to deliver gait therapy, which, in contrast to previous approaches, takes advantage of the concept of passive walkers and the natural dynamics of the lower extremity in order to deliver more "ecological" therapy. We also discuss the closed-loop control scheme, which enables safe and efficient operation of the device, and present the initial feasibility tests with unimpaired subjects.

An MR safe apparatus is important for the for monitoring of tasks in the magnetic resonance (MR) environment. This paper describes the development of an MR safe movement evaluation system to measure the hand grasp and elbow flexion/extension movements. The system will be used to monitor motor performance in the fMRI environment and assess functional and motor impairment level pre and post robot-assisted therapy.

The importance on walking for health is growing in elder dominated society. We have been developing a new mobility "Tread-Walk 1 (TW-1)" controlled by walking movement. The device uses active treadmill velocity control, which allows the user to walk on the treadmill at any desired velocity. In this paper, the walking movements on the TW-1 were kinematically analyzed and compared with the walking movements on a traditional constant-velocity treadmill and on flat ground. The results showed that the walking pattern on the TW-1 was somewhat similar to that on a constant-velocity treadmill and on flat ground; however, the flexion angle of the hip joint and the dorsiflexion and plantaflexion angles of the ankle joint during TW-1 walking were larger. It also was shown that the foot applied a stronger kicking force to the belt at toe-off and the foot clearance on the TW-1 was larger than that on the constant-velocity treadmill and on flat ground. Therefore, the walking patterns in the swing and stance phase on the TW-1 are little different. However, the walking movements based on the TW-1 active belt control are valuable from the viewpoints of motion training.

In this paper, a handle-electrode system is proposed for obtaining the heart rate of a user while riding a bicycle. The system was designed to measure the user's heart rate by only gripping the handle of a bicycle. Three electrodes made from conductive cloth were adhered to the handle. A method detecting heart-rate from the obtained electrocardiogram was also proposed. To assess the applicability of the proposed system, a simple experiment was performed. The experiment was performed in four conditions of road surfaces; lawn, asphalt, a tiled, and an uneven road. Experimental result suggests that the proposed system can be useful for obtaining R waves while riding a bicycle.

We proposed the calculation method of the ventilation threshold using the noncontact respirometry under pedal stroke motion. By the simultaneous measurement with the expiration gas analyzer, we examined the effectiveness of the proposal method. There was high correlation over 0.8 between ventilation variations calculated by our proposed method and the expiration gas analyzer. On the other hand, the correlation between ventilation thresholds calculated by our proposed method and the expiration gas analyzer is 0.735. In this experiment, the sufficient examination seemed to be difficult on the correlation, since the difference between the systemic aerobic capacities of the examinees is small.

The purpose of this study is to determine an individual physiological signal and based on the information; develop equipment that will encourage the efficiency of exercise. To evaluate the practical use of equipment an experiment is carried out. The signal of twenty adult male is determined under condition of Exercise Stress Test. Measured physiological signals are ECG from ears, chest (Lead I), PPG from earlap, activity from ear and arm, and the body skin temperature of arm. For ECG data, there are two signals: one is ear-arm signal, and the other is chest (Lead I) signal. When compare those two, ear-arm detection rate shows 92.08% detection, and 93.13% at chest. The error rate occurred average 0.035(+/-0.014) seconds and 0.026(+/-0.017) seconds. For PPG, we can reduce the influence of motion artifact by Autocorrelation method, and as a result, peak detection rate increased from 94.3% to 98.4%, decreased the error rate with 0.058+/-0.076 to 0.023+/-0.031, Also, we certified that if the speed and elevation of the treadmill increase, physical activity increase, and the body temperature gets decreased. Upon this consequence, we developed a physiological data acquisition system that is convenient to user while they are exercising.

We proposed the non-contact measurement method of the respiratory movement under pedal stroke motion, by the application of optical technique. By the simultaneous measurement with the expiration gas analyzer, we examined the effectiveness of the proposal method. As the results, we clarified that the calculated value obtained by our proposal method is highly correlated with the tidal volume expiration measured by the expiration gas analyzer.

Walking distance estimation is an important issue in areas such as gait analysis, sport training or pedestrian localization. A natural location for portable inertial sensors for gait monitoring is to attach them to the user shoes. Step length can be computed by means of a biaxial accelerometer and a gyroscope on the sagittal plane. But estimations based on the direct signal integration are prone to error. This paper shows the results achieved by using a multisensor model approach to reduce uncertainty. Unbounded growth of error is reduced by means of sensor fusion techniques. The method has been tested, and early experimental results show that it provides an estimation of the walking distance with a standard deviation smaller than with single IMU similar systems.

Efforts have been made to measure the distance traveled by humans in motion, in ways that are compact and accurate, for a long time. There are several ways to measure the distance moved by walking or running in daily life, some of which already use commercial products, but those methods are inaccurate. In this study, a new method is provided using ultrasonic sensors, and this is the fundamental study. The newly devised 'Portable Walking Distance Measurement System' was developed using ultrasonic wave characteristics and has approximately 90% accuracy. This result provides an opportunity to estimate human activities and the developed system would provide more comfort and an exact way to measure the walking distance in daily life and could be applied to exercise.