Effects of human limb gestures on galvanic coupling intra-body communication for advanced healthcare system

A Low-Cost Electronic System for Human-Body Communication

Human-body communication (HBC) has increasingly gained attention from academia and industry. Most current works focus on characterizing the use of human-body tissues as a physical medium to enable reliable communication. However, designing coupling hardware and communication circuits for reliable data transmission (e.g., high throughput and low latency) is a demanding task, especially for achieving a compact full electronic implementation. For this purpose, there are few commercial devices, mainly differential probes and balun transformers, employed with electrical analysis instruments such as oscilloscopes and vector network analyzers. Although these devices are widely used, they are expensive and are difficult to miniaturize and integrate into real-world HBC-specific applications (e.g., data security). This article presents a low-cost electronic system that transfers collected data using a secondary channel: the ionic environment (the primary channel would be the wireless environment). We design an electronic system as an experimental setup for studying HBC, allowing the communication between instruments, sensors, and actuators by human-body tissues. The experimental evaluation of the proposed system follows (i) a phantom composed of saline (0.9%) and (ii) a real human forearm through adhesive surface electrodes.

Measuring upper limb movement to analyze intra-body communication channel attenuation characteristics

BACKGROUND

This experiment was designed to study the respective effects of the closed-state human palm and dynamic arm bending on intra-body communication channel attenuation.

METHODS

We selected the right upper arm of a healthy adult male as the experimental object to measure channel attenuation variation in a closed or open palm, and when the arm was bent, so as to analyze channel characteristics.

CONCLUSIONS

The experiment showed that, in a quasi-static stable system, the effects of a closed palm on channel attenuation were negligibly minimal. In contrast, the physiological signal of the living body significantly interfered with the channel in the low-frequency mode. In the dynamic arm-bending experiment, we found that the attenuation variation range corresponds to the intersection angle (90∘⩽θ⩽ 180∘) of the upper arm and forearm; these results provide the basis for the establishment of a theoretical model.

Non-Uniform Sample Assignment in Training Set Improving Recognition of Hand Gestures Dominated with Similar Muscle Activities

So far, little is known how the sample assignment of surface electromyogram (sEMG) features in training set influences the recognition efficiency of hand gesture, and the aim of this study is to explore the impact of different sample arrangements in training set on the classification of hand gestures dominated with similar muscle activation patterns. Seven right-handed healthy subjects (24.2 ± 1.2 years) were recruited to perform similar grasping tasks (fist, spherical, and cylindrical grasping) and similar pinch tasks (finger, key, and tape pinch). Each task was sustained for 4 s and followed by a 5-s rest interval to avoid fatigue, and the procedure was repeated 60 times for every task. sEMG were recorded from six forearm hand muscles during grasping or pinch tasks, and 4-s sEMG from each channel was segmented for empirical mode decomposition analysis trial by trial. The muscle activity was quantified with zero crossing (ZC) and Wilson amplitude (WAMP) of the first four resulting intrinsic mode function. Thereafter, a sEMG feature vector was constructed with the ZC and WAMP of each channel sEMG, and a classifier combined with support vector machine and genetic algorithm was used for hand gesture recognition. The sample number for each hand gesture was designed to be rearranged according to different sample proportion in training set, and corresponding recognition rate was calculated to evaluate the effect of sample assignment change on gesture classification. Either for similar grasping or pinch tasks, the sample assignment change in training set affected the overall recognition rate of candidate hand gesture. Compare to conventional results with uniformly assigned training samples, the recognition rate of similar pinch gestures was significantly improved when the sample of finger-, key-, and tape-pinch gesture were assigned as 60, 20, and 20%, respectively. Similarly, the recognition rate of similar grasping gestures also rose when the sample proportion of fist, spherical, and cylindrical grasping was 40, 30, and 30%, respectively. Our results suggested that the recognition rate of hand gestures can be regulated by change sample arrangement in training set, which can be potentially used to improve fine-gesture recognition for myoelectric robotic hand exoskeleton control.

Evaluation of Propagation Characteristics Using the Human Body as an Antenna

In this paper, an inhomogeneous human body model was presented to investigate the propagation characteristics when the human body was used as an antenna to achieve signal transmission. Specifically, the channel gain of four scenarios, namely, (1) both TX electrode and RX electrode were placed in the air, (2) TX electrode was attached on the human body, and RX electrode was placed in the air, (3) TX electrode was placed in the air, and RX electrode was attached on the human body, (4) both the TX electrode and RX electrode were attached on the human body, were studied through numerical simulation in the frequency range 1 MHz to 90 MHz. Furthermore, the comparisons of input efficiency, accepted efficiency, total efficiency, absorption power of human body, and electric field distribution of different distances of four aforementioned scenarios were explored when the frequency was at 44 MHz. In addition, the influences of different human tissues, electrode position, and the distance between electrode and human body on the propagation characteristics were investigated respectively at 44 MHz. The results showed that the channel gain of Scenario 4 was the maximum when the frequency was from 1 MHz to 90 MHz. The propagation characteristics were almost independent of electrode position when the human body was using as an antenna. However, as the distance between TX electrode and human body increased, the channel gain decreased rapidly. The simulations were verified by experimental measurements. The results showed that the simulations were in agreement with the measurements.

The Modeling and Simulation of the Galvanic Coupling Intra-Body Communication via Handshake Channel

Intra-body communication (IBC) is a technology using the conductive properties of the body to transmit signal, and information interaction by handshake is regarded as one of the important applications of IBC. In this paper, a method for modeling the galvanic coupling intra-body communication via handshake channel is proposed, while the corresponding parameters are discussed. Meanwhile, the mathematical model of this kind of IBC is developed. Finally, the validity of the developed model has been verified by measurements. Moreover, its characteristics are discussed and compared with that of the IBC via single body channel. Our results indicate that the proposed method will lay a foundation for the theoretical analysis and application of the IBC via handshake channel.