Mechanical and structural properties of major ampullate silk from spiders fed carbon nanomaterials.

The dragline silk of spiders is of particular interest to science due to its unique properties that make it an exceptional biomaterial that has both high tensile strength and elasticity. To improve these natural fibers, researchers have begun to try infusing metals and carbon nanomaterials to improve mechanical properties of spider silk. The objective of this study was to incorporate carbon nanomaterials into the silk of an orb-weaving spider, Nephila pilipes, by feeding them solutions containing graphene and carbon nanotubes. Spiders were collected from the field and in the lab were fed solutions by pipette containing either graphene sheets or nanotubes. Major ampullate silk was collected and a tensile tester was used to determine mechanical properties for pre- and post-treatment samples. Raman spectroscopy was then used to test for the presence of nanomaterials in silk samples. There was no apparent incorporation of carbon nanomaterials in the silk fibers that could be detected with Raman spectroscopy and there were no significant improvements in mechanical properties. This study represents an example for the importance of attempting to replicate previously published research. Researchers should be encouraged to continue to do these types of investigations in order to build a strong consensus and solid foundation for how to go forward with these new methods for creating novel biomaterials.

Balance Control and Energetics of Powered Exoskeleton-Assisted Sit-to-Stand Movement in Individuals With Paraplegic Spinal Cord Injury.

OBJECTIVE: To quantify the effects of initial hip angle and angular hip velocity settings of a lower-limb wearable robotic exoskeleton (WRE) on the balance control and mechanical energy requirements in patients with paraplegic spinal cord injuries (SCIs) during WRE-assisted sit-to-stand (STS). DESIGN: Observational, cross-sectional study. SETTING: A university hospital gait laboratory with an 8-camera motion analysis system, 3 forceplates, a pair of instrumented crutches, and a WRE. PARTICIPANTS: Patients (N=12) with paraplegic SCI. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The inclination angle (IA) of the body's center of mass (COM) relative to the center of pressure (COP), and the rate of change of IA (RCIA) for balance control, and the mechanical energy and forward COM momentum before and after seat-off for energetics during WRE-assisted STS were compared between conditions with 2 initial hip angles (105° and 115°) and 3 initial hip angular velocities (800, 1000, 1200 rpm). RESULTS: No interactions between the main factors (ie, initial hip angle vs angular velocity) were found for any of the calculated variables. Greater initial hip angle helped the patients with SCI move the body forward with increased COM momentum but reduced RCIA (P<.05). With increasing initial angular hip velocity, the IA and RCIA after seat-off (P<.05) increased linearly while total mechanical energy reduced linearly (P<.05). CONCLUSIONS: The current results suggest that a greater initial hip angle with smaller initial angular velocity may provide a favorable compromise between momentum transfer and balance of the body for people with SCI during WRE-assisted STS. The current data will be helpful for improving the design and clinical use of the WRE.

The effects of gait training using powered lower limb exoskeleton robot on individuals with complete spinal cord injury.

BACKGROUND: Powered exoskeleton can improve the mobility for people with movement deficits by providing mechanical support and facilitate the gait training. This pilot study evaluated the effect of gait training using a newly developed powered lower limb exoskeleton robot for individuals with complete spinal cord injury (SCI). METHODS: Two participants with a complete SCI were recruited for this clinical study. The powered exoskeleton gait training was 8 weeks, 1 h per session, and 2 sessions per week. The evaluation was performed before and after the training for (1) the time taken by the user to don and doff the powered exoskeleton independently, (2) the level of exertion perceived by participants while using the powered exoskeleton, and (3) the mobility performance included the timed up-and-go test, 10-m walk test, and 6-min walk test with the powered exoskeleton. The safety of the powered exoskeleton was evaluated on the basis of injury reports and the incidence of falls or imbalance while using the device. RESULTS: The results indicated that the participants were donning and doffing the powered lower limb exoskeleton robot independently with a lower level of exertion and walked faster and farther without any injury or fall incidence when using the powered exoskeleton than when using a knee-ankle-foot orthosis. Bone mineral densities was also increased after the gait training. No adverse effects, such as skin abrasions, or discomfort were reported while using the powered exoskeleton. CONCLUSIONS: The findings demonstrated that individuals with complete SCI used the powered lower limb exoskeleton robot independently without any assistance after 8 weeks of powered exoskeleton gait training. TRIAL REGISTRATION: Trial registration: National Taiwan University Hospital. TRIAL REGISTRATION NUMBER: 201210051RIB . Name of registry: Hui-Fen Mao. URL of registry: Not available. Date of registration: December 12th, 2012. Date of enrolment of the first participant to the trial: January 3rd, 2013.

A kinematic human-walking model for the normal-gait-speed estimation using tri-axial acceleration signals at waist location.

This study aims at estimating the human walking speed using wearable accelerometers by proposing a novel virtual inverted pendulum model. This model not only keeps the important characteristics of both the biped rolling-foot and the inverted pendulum model, but also makes the speed estimation feasible using human body acceleration. Rather than using statistical methods, the proposed kinematic walking model enables calibration of the parameters during walking using only one tri-axial accelerometer on the waist that collects the user's body acceleration. In addition, this model also includes the effect of rotation of the waist within a walking cycle, which improves the estimation accuracy. Experimental results for a group of humans show a 0.58% absolute error mean and 0.72% error deviation, which is far better than the results of other known studies with accelerometers mounted on the upper body.

A wireless gait analysis system by digital textile sensors.

This paper studies the feasibility of spatio-temporal gait analysis based upon digital textile sensors. Digitized legs and feet patterns of healthy subjects and their relations with spatio-temporal gait parameters were analyzed. In the first experiment, spatio-temporal gait parameters were determined during over ground walking. In the second experiment, predicted running, backward walking, walking up stairs and walking down stairs parameters were determined. From the results of the experiments, it is concluded that, for healthy subjects, the duration of subsequent stride cycles and left/right steps, the estimations of step length, cadence, walking speed, central of pressure and central of mass trajectory, can be obtained by analyzing the digital signals from the textile sensors on pants and socks. These parameters are easily displayed in several different graphs allowing the user to view the parameters during gait. Finally, the digital data are easily to analyze the feature of activity recognition.

Robust speaker's location detection in a vehicle environment using GMM models.

Abstract-Human-computer interaction (HCI) using speech communication is becoming increasingly important, especially in driving where safety is the primary concern. Knowing the speaker's location (i.e., speaker localization) not only improves the enhancement results of a corrupted signal, but also provides assistance to speaker identification. Since conventional speech localization algorithms suffer from the uncertainties of environmental complexity and noise, as well as from the microphone mismatch problem, they are frequently not robust in practice. Without a high reliability, the acceptance of speech-based HCI would never be realized. This work presents a novel speaker's location detection method and demonstrates high accuracy within a vehicle cabinet using a single linear microphone array. The proposed approach utilize Gaussian mixture models (GMM) to model the distributions of the phase differences among the microphones caused by the complex characteristic of room acoustic and microphone mismatch. The model can be applied both in near-field and far-field situations in a noisy environment. The individual Gaussian component of a GMM represents some general location-dependent but content and speaker-independent phase difference distributions. Moreover, the scheme performs well not only in nonline-of-sight cases, but also when the speakers are aligned toward the microphone array but at difference distances from it. This strong performance can be achieved by exploiting the fact that the phase difference distributions at different locations are distinguishable in the environment of a car. The experimental results also show that the proposed method outperforms the conventional multiple signal classification method (MUSIC) technique at various SNRs.