Periodic Movements Research Articles

A New Iterative Algorithm for Magnetic Motion Tracking

Motion analysis is of great interest to a variety of applications, such as virtual and augmented reality and medical diagnostics. Hand movement tracking systems, in particular, are used as a human–machine interface. In most cases, these systems are based on optical or acceleration/angular speed sensors. These technologies are already well researched and used in commercial systems. In special applications, it can be advantageous to use magnetic sensors to supplement an existing system or even replace the existing sensors. The core of a motion tracking system is a localization unit. The relatively complex localization algorithms present a problem in magnetic systems, leading to a relatively large computational complexity. In this paper, a new approach for pose estimation of a kinematic chain is presented. The new algorithm is based on spatially rotating magnetic dipole sources. A spatial feature is extracted from the sensor signal, the dipole direction in which the maximum magnitude value is detected at the sensor. This is introduced as the “maximum vector”. A relationship between this feature, the location vector (pointing from the magnetic source to the sensor position) and the sensor orientation is derived and subsequently exploited. By modelling the hand as a kinematic chain, the posture of the chain can be described in two ways: the knowledge about the magnetic correlations and the structure of the kinematic chain. Both are bundled in an iterative algorithm with very low complexity. The algorithm was implemented in a real-time framework and evaluated in a simulation and first laboratory tests. In tests without movement, it could be shown that there was no significant deviation between the simulated and estimated poses. In tests with periodic movements, an error in the range of 1° was found. Of particular interest here is the required computing power. This was evaluated in terms of the required computing operations and the required computing time. Initial analyses have shown that a computing time of 3 μs per joint is required on a personal computer. Lastly, the first laboratory tests basically prove the functionality of the proposed methodology.

Engineering of a Bio-Inspired Tiltable Oscillating Fin Submersible Thruster

Oscillating fins are devices designed to produce thrust through periodic undulating movements. However, these structures lack flexibility and often provide thrust in only one fixed direction. Observation and biological references suggest that the dorsal fin rays of seahorses can tilt longitudinally in the spine direction, changing the thrust direction. This study aims to analyze the dynamic effects of seahorse dorsal fin inclining and design a flexible bionic thruster based on this principle. Computational fluid dynamics analysis hypothesizes that fin inclination controls the net force direction in the vertical plane. A force sensor and pulley system test platform were constructed to examine the influences of wave features and the inclination angle on thrust in both vertical and horizontal directions, with discrete fin surfaces used to eliminate force interference. Force testing and snapshots indicate that wave velocity positively impacts net force magnitude, while fin inclination allows for control over force orientation. This tiltable oscillating fin thruster possesses more degrees of freedom, leading to better flexibility and providing controllable thrust orientation.

Damage and removal behaviors of indium phosphide crystals involved in ultrasonic vibration-assisted AFM machining

Indium phosphide (InP) crystals exhibit a propensity for brittle damage during machining, categorizing them as challenging materials due to their inherent brittleness and pronounced anisotropy. Atomic force microscopy (AFM) machining serves as a crucial approach for achieving low-damage removal of such brittle crystals. Molecular dynamics simulations were conducted to investigate the vibration-assisted AFM machining of InP crystals, systematically exploring the effects of scratching force, stress distribution, and subsurface damage. The findings revealed that plastic deformation of InP crystals during vibration-assisted AFM scratching was primarily governed by mechanisms including stress-induced amorphization transitions, phase transformations, dislocations, stacking faults, and lattice distortions. Compared to conventional AFM machining, vibration-assisted AFM machining had a smaller average contact area and maintained a periodic movement pattern of contact-separation. This induced the change of chip removal from piling up in front of the cutting tool to uniform flow to both sides. Employing appropriate vibration parameters in vibration-assisted AFM significantly diminished the scratching force, stress, dislocation length, and subsurface damage depth. These results not only elucidate the material removal and damage mechanisms of InP crystals at atomic and close-to-atomic scales, but also offer theoretical guidance for parameter optimization in the vibration-assisted AFM machining of other soft and brittle crystals.

Improvement of the Estimation of the Vertical Crustal Motion Rate at GNSS Campaign Stations Based on the Information of GNSS Reference Stations

With the enrichment of GNSS data and the improvement in data processing accuracy, GNSS technology has been widely applied in fields such as crustal deformation. The Crustal Movement Observation Network of China (CMONOC) has provided decades of Global Navigation Satellite System (GNSS) data and related data products for crustal deformation research on the Chinese mainland. The coordinate time series of continuously observed reference stations contain abundant information on crustal movements. In contrast, the coordinate time series of periodically observed campaign stations have limited data, making it difficult to separate or remove instantaneous non-tectonic movements from the time series, as performed with reference stations, to obtain a stable and reliable crustal movement velocity field. To address this issue, this paper proposes a method to improve the estimation of crustal movement velocity at campaign stations using the information of neighboring reference stations. This method constructs a Delaunay triangulation of reference stations and fits the periodic movement of each campaign station using an inverse distance weighted interpolation algorithm based on the reference station information. The crustal movement velocity of the campaign stations is then estimated after removing the periodic movement. This method was verified by its application to the estimation of the vertical motion rate at some reference and campaign stations in Yunnan Province. The results show that the accuracy of vertical motion rate estimation for virtual and real campaign stations improved by an average of 24.4% and 9.6%, respectively, demonstrating the effectiveness of the improved method, which can be applied to estimate crustal movement velocity at campaign stations in other areas.

Biometric Vibration Signal Detection Devices for Swallowing Activity Monitoring

Swallowing is a complex neuromuscular activity regulated by the autonomic central nervous system, and impairment can lead to dysphagia, which is difficulty in swallowing. This research presents a novel approach that utilizes wireless, wearable technology for the continuous mechano-acoustic tracking of respiratory activities and swallowing. To address the challenge of accurately tracking swallowing amidst potential confounding activities or significant body movements, we employ two accelerometers. These accelerometers help distinguish between genuine swallowing events and other activities. By monitoring movements and vibrations through the skin surface, the developed device enables non-intrusive monitoring of swallowing dynamics and respiratory patterns. Our focus is on the development of both the wireless skin-interfaced device and an advanced algorithm capable of detecting swallowing dynamics in conjunction with respiratory phases. The device and algorithm demonstrate robustness in detecting respiratory patterns and swallowing instances, even in scenarios where users exhibit periodic movements due to disease or daily activities. Furthermore, peak detection using an adaptive threshold automatically adjusts to an individual’s signal strength, facilitating the detection of swallowing signals without the need for individual adjustments. This innovation has significant potential for enhancing patient training and rehabilitation programs aimed at addressing dysphagia and related respiratory issues.

Learning periodic skills for robotic manipulation: Insights on orientation and impedance

Many daily tasks exhibit a periodic nature, necessitating that robots possess the ability to execute them either alone or in collaboration with humans. A widely used approach to encode and learn such periodic patterns from human demonstrations is through periodic Dynamic Movement Primitives (DMPs). Periodic DMPs encode cyclic data independently across multiple dimensions of multi-degree of freedom systems. This method is effective for simple data, like Cartesian or joint position trajectories. However, it cannot account for various geometric constraints imposed by more complex data, such as orientation and stiffness. To bridge this gap, we propose a novel periodic DMP formulation that enables the encoding of periodic orientation trajectories and varying stiffness matrices while considering their geometric constraints. Our geometry-aware approach exploits the properties of the Riemannian manifold and Lie group to directly encode such periodic data while respecting its inherent geometric constraints. We initially employed simulation to validate the technical aspects of the proposed method thoroughly. Subsequently, we conducted experiments with two different real-world robots performing daily tasks involving periodic changes in orientation and/or stiffness, i.e., operating a drilling machine using a rotary handle and facilitating collaborative human–robot sawing.

Introducing a New Method for Studying the Effects of Movement Synchrony in Virtual Reality.

This study introduces a new method to create virtual reality (VR) environments for studying synchrony in human body movements and their prosocial effects. Previous studies have shown the positive effects of synchrony, but more controlled and ecologically valid paradigms are needed to explore these effects deeper and translate them to the therapeutic domain. A total of 82 healthy subjects participated in this study. They performed simple periodic hand movements in a virtual environment with a virtual character (VC) mimicking them. We used inverse kinematics (IKs) to create character movements. The VCs mimic the participants after a short delay in the synchronous group and after a great delay in the nonsynchronous group. The subjective feeling of synchrony and social closeness was measured using a set of rating questionnaires. The participants in the synchronous group reported more synchrony than the nonsynchronous group. The degree of social closeness between the two groups was not significantly different; however, there was a significant positive correlation between the reported degree of synchrony and social closeness within each group. Using a simple VR environment in which body movements are simulated by IKs can engender the feeling of synchrony and exert its prosocial effects.

Development of elbow rehabilitation device with iterative learning control and internet of things

In this study, we present a novel approach for rehabilitation devices through the design of an active elbow joint orthosis, inspired by the fundamental principles of robotic exoskeletons. The device not only enables home-based usage but also facilitates the transmission of exercise data from patients to physiotherapists via the Internet of Things (IoT) device. This approach offers the possibility of increased therapy sessions for each patient while allowing physiotherapists access to data for real-time or subsequent analyses, thereby establishing a database. This permits a single physiotherapist to manage multiple patients more effectively. The developed mobile application within this research incorporates a distinct entry interface for both patients and physiotherapists. Maximum force and position values generated during each exercise period are displayed within the application. The device enables active exercise with a single degree of freedom at the elbow joint and is equipped with force sensors to ensure safety against potential high-shear forces. Furthermore, it can be worn on the upper extremity using adjustable Velcro straps to accommodate users with varying arm circumferences. Specifically, this system amalgamates two primary components: a microcontroller operating control algorithms and IoT technology, and a smartphone application containing interfaces for physiotherapists and users undergoing therapy. The control design of the device employs a P-Type Iterative Learning Control (ILC) due to periodic exercise movements, reducing the error norm by approximately 20% during each exercise period (excluding the initial period). The controller consistently diminishes error values with each iteration, ultimately converging to zero. Throughout an exercise lasting around 3 minutes, the average error norm is recorded as 0.229⁰. In essence, this study presents a pioneering approach that sets itself apart from other research by minimizing shear forces and errors through a specialized controller, all while enabling remote, home-based rehabilitation under expert supervision.

Energy-based high frequency oscillation control of linear drives

Linear electromagnetic actuators realizing periodic oscillations have gained significant importance in the compressor and pump technology. This is due to the need of compact drive units to increase the power density of modern pumps and compressors. This work presents an energy-based control approach for harmonic oscillations of linear electromagnetic drives and analyzes the functionality and performance of the oscillation control for periodic actuator movements up to 250 Hz. To obtain a more robust control behavior, the control structure needs to be decoupled, with an amplitude and phase component using a periodical harmonic carrier function. This approach avoids a standstill of the actuator by constantly triggering an oscillation at the fundamental frequency of the mechanical system. The presented control approach is especially beneficial for oscillatory systems which need to adapt their oscillation frequency to mechanical loads.

Characteristics of blood flow velocity in the radial artery and finger capillaries using magnetoplethysmogram and photoplethysmogram

The Hall element and optical sensor, which can detect the magnetic field change caused by the minute fluctuations of the permanent magnet according to the periodic movement of the radial artery and the light absorption and reflection intensity according to the change in wrist blood flow, respectively, are used as key elements in digital healthcare devices. The pulse waves of the radial artery inside the wrist were measured and analyzed using a clip-type pulsimeter, magnetoplethysmogram (MPG). The pulse wave, which is the change in blood flow obtained by photoplethysmogram (PPG), was measured on the dorsal side of the wrist or the fingers simultaneously with MPG. The ABFV (artery blood flow velocity) is a few ten cm/s as DH (distance between MPG and PPG) divided by ΔT(a) which is the time difference between the first peaks of MPG and PPG waveforms on the dorsal side of the wrist. The PBFV (peripheral blood flow velocity) is a few mm/s as LH (hand length) divided by ΔT(p), which is the time difference between the first peak of MPG waveform and the third peak PPG waveform on the finger. For four subjects of 20s, SPWV was approximately 0.98∼1.19 m/s, ABFV in the radial artery was approximately 0.40∼0.44 m/s, and finger capillary PBFV was approximately 6.3∼8.6 cm/s. These results show reasonable values similar to the blood velocity of many blood vessels flowing through the human body.

Truncated FRMD7 proteins in congenital Nystagmus: novel frameshift mutations and proteasomal pathway implications

Idiopathic congenital nystagmus (ICN) manifests as involuntary and periodic eye movements. To identify the genetic defect associated with X-linked ICN, Whole Exome Sequencing (WES) was conducted in two affected families. We identified two frameshift mutations in FRMD7, c.1492dupT/p.(Y498Lfs*15) and c.1616delG/p.(R539Kfs*2). Plasmids harboring the mutated genes and qPCR analysis revealed mRNA stability, evading degradation via the NMD pathway, and corroborated truncated protein production via Western-blot analysis. Notably, both truncated proteins were degraded through the proteasomal (ubiquitination) pathway, suggesting potential therapeutic avenues targeting this pathway for similar mutations. Moreover, we conducted a comprehensive analysis, summarizing 140 mutations within the FRMD7 gene. Our findings highlight the FERM and FA structural domains as mutation-prone regions. Interestingly, exons 9 and 12 are the most mutated regions, but 90% (28/31) mutations in exon 9 are missense while 84% (21/25) mutations in exon 12 are frameshift. A predominant occurrence of shift code mutations was observed in exons 11 and 12, possibly associated with the localization of premature termination codons (PTCs), leading to the generation of deleterious truncated proteins. Additionally, our conjecture suggests that the loss of FRMD7 protein function might not solely drive pathology; rather, the emergence of aberrant protein function could be pivotal in nystagmus etiology. We propose a dependence of FRMD7 protein normal function primarily on its anterior domain. Future investigations are warranted to validate this hypothesis.

Generalized sequential state equation method for moving subsystem-induced structural parametric resonance

Parametric excitation is a unique type of excitation that arises from the time-varying parameters of a dynamical system, typically induced by the periodic movements of the system components. However, the structure-moving subsystems problem creates a new type of parametric excitation where the subsystems do not have exact periodic movements. Under the circumstances, dimension of the mathematical model of such a system exhibits time dependency, which prohibits the employment of conventional analytical methods to predict its stability. In this paper, we propose a novel Generalized Sequential State Equation Method that provides a distinct solution framework for analysis of the subsystem-induced parametric resonance. With the time-domain system partition and state mapping, the proposed method reconfigures the coupled system with a sequence of state space equations and solves them chronologically. The proposed method relaxes the single-subsystem-assumption in its original form and applies to a general scenario where the subsystems travel with arbitrary characteristic period. With the proposed method, occurrences of the subsystem-induced parametric resonance are precisely predicted via a set of analytical stability criteria and the steady state response is determined in an exact analytical form.

Learning an Autonomous Dynamic System to Encode Periodic Human Motion Skills.

Learning an autonomous dynamic system (ADS) encoding human motion rules has been shown as an effective way for human motion skills transfer. However, most existing approaches focus on goal-directed motion skills transfer, and the study on periodic motion skills transfer is rare. One popular approach for periodic motion skills transfer is learning periodic dynamic movement primitive (DMP); however, periodic DMP is sensitive to spatial disturbances due to the introduction of the phase parameters. To solve this issue, this brief presents a novel approach to learn an ADS with a stable limit cycle without introducing phase parameters. First, a data-driven Lyapunov function (energy function) is learned, such that one of its level surfaces is consistent with periodic human demonstration trajectories. Then, an ADS is learned by sequentially solving energy function-related constrained optimization problems. With a proper design of constraint functions, we can ensure that the trajectory generated by the ADS will converge to an energy function-level surface, of which the shape is similar to periodic human demonstration trajectories. Experiments are conducted to show the effectiveness of the proposed approach (PA).

Chip-integrated non-mechanical microfluidic pump driven by electrowetting on dielectrics.

A microfluidic pump is presented that generates its pumping action via the EWOD (electrowetting-on-dielectric) effect. The flow is generated by the periodic movement of liquid-vapor interfaces in a large number (≈106) of microcavities resulting in a volume change of approx. 0.5 pl per cavity per pump stroke. The total flow resulting from all microcavities adds up to a few hundred nanolitres per cycle. Passive, topologically optimized, non-mechanical Tesla valves are used to rectify the flow. As a result, the micropump operates without any moving components. The dimensioning, fabrication, and characterization process of the micropump are described. Device fabrication is done using conventional manufacturing processes from microsystems technology, enabling cost-effective mass production on wafer-level without additional assembly steps like piezo chip-level bonding, etc. This allows for direct integration into wafer-based microfluidic or lab-on-a-chip applications. Furthermore, first measurement results obtained with prototypes of the micropump are presented. The voltage- and frequency-dependent pump performance is determined. The measurements show that a continuous flow rate larger than 0.2 ml min-1 can be achieved at a maximum pump pressure larger than 12 mbar.

Intravital microscopic thermometry of rat mammary epithelium by fluorescent nanodiamond.

Quantum sensing using the fluorescent nanodiamond (FND) nitrogen-vacancy center enables physical/chemical measurements of the microenvironment, although application of such measurements in living mammals poses significant challenges due to the unknown biodistribution and toxicity of FNDs, the limited penetration of visible light for quantum state manipulation/measurement, and interference from physiological motion. Here, we describe a microenvironmental thermometry technique using FNDs in rat mammary epithelium, an important model for mammary gland biology and breast cancer research. FNDs were injected directly into the mammary gland. Microscopic observation of mammary tissue sections showed that most FNDs remained in the mammary epithelium for at least 8 weeks. Pathological examination indicated no obvious change in tissue morphology, suggesting negligible toxicity. Optical excitation and detection were performed through a skin incision. Periodic movements due to respiration and heartbeat were mitigated by frequency filtering of the signal. Based on these methods, we successfully detected temperature elevation in the mammary epithelium associated with lipopolysaccharide-induced inflammation, demonstrating the sensitivity and relevance of the technique in biological contexts. This study lays the groundwork for expanding the applicability of quantum sensing in biomedical research, providing a tool for real-time monitoring of physiological and pathological processes.

Hydroperiod modulates early growth and biomass partitioning in Rhizophora mangle L.

In mangrove forests, the hydroperiod is strongly related to tidal dynamics, where the periodic oceanic water movement regulates the level, duration, and frequency of the flooding events. In fringe mangrove forests, Rhizophora mangle propagules deal with variable hydroperiod conditions that sometimes compromise their survival. To disentangle the combined effects of duration and intensity of flooding on physiological and growth variables, we imposed a continuous experiment with three levels of flooding and four flooding durations on seedlings of R. mangle. We collected data at 3 and 6.5 months after exposure to the treatments. Propagule reserves allowed plants to evade the effects of the flood level after a 3-month treatment period. After a 6.5-month exposure, physiology and growth were modulated by the flooding time. Individual plants had higher stem length and lower root and total biomass at prolonged and high flooding levels compared to any other flooding combinations. In both ages, the highest total plant biomass was exhibited in the medium flooding levels and 6 h flooding duration. The plasticity index was higher for morphological and biomass variables than for physiological variables. The high morphological plasticity of R. mangle plants constitutes a competitive advantage to colonize flooded sites in fringed mangrove areas. Our results identify schemes to improve the success of mangrove restoration plans, a critical tool for carbon sequestration and ecosystem service provision.

A novel motorized office chair causes low-amplitude spinal movements and activates trunk muscles: A cross-over trial.

Inactivity and long periods of sitting are common in our society, even though they pose a health risk. Dynamic sitting is recommended to reduce this risk. The purpose of this study was to investigate the effect of continuous passive motion (CPM) conducted by a novel motorized office chair on lumbar lordosis and trunk muscle activation, oxygen uptake and attentional control. Randomized, single-session, crossover with two periods/conditions. Twenty office workers (50% women) sat for one hour on the motorized chair, one half with CPM, the other not. The starting condition (CPM/no CPM) was switched in half of the sample. The participants were equipped with a spirometric cart, surface EMG, the Epionics SPINE system and performed a computer-based test for attentional control (AX-CPT). Outcomes were lumbar sagittal movements and posture, number of trunk muscle activations, attentional control and energy expenditure. The CPM of the chair causes frequent low-amplitude changes in lumbar lordosis angle (moved: 498 ± 133 vs. static: 45 ± 38) and a higher number of muscle activations. A periodic movement pattern of the lumbar spine according to the movement of the chair was observed in every participant, although, sitting behavior varied highly between individuals. Attentional control was not altered in the moved condition (p = .495; d = .16). Further, oxygen uptake did not increase higher than 1.5 MET. The effects of the motorized chair can be particularly useful for people with static sitting behavior. Further studies should investigate, whether CPM provides the assumed beneficial effects of dynamic sitting on the spine.

The Coupling Effects Between Floating Insulation Plates and the Thermal Convection in their Bottoms---- An Understanding of Continental Drift

The phenomenon of dumpling drift was discovered during a cooking process, which triggered our thinking of the continental drift. After refining the existing common problems, an experiment on the thermal convection interaction between the floating heat insulation plates and the bottoms is designed. Through controlling variables, this paper investigates the floating patterns of floating insulation plates of different sizes on a thermally convective surface and the principles behind them. The findings show that the appropriate sizing of a floating plate can result in the manifestation of cyclic reciprocating movement on the water’s surface. The periodic movement observed in this phenomenon can be attributed to the obstruction of heat exchange between the water surface and the surrounding air by the floating plate. Consequently, alterations in the direction of water flow induce corresponding shifts in water temperature, which subsequently affect the movement direction of the floating plate. The final outcome is characterized by a periodic reciprocal movement of the floating plate as it interacts with the heat convection occurring at the bottom. Floating plates that are either undersized or oversized would remain stationary without exhibiting any cyclic drift. The decrease in water depth leads to a diminished thermal drive, thereby amplifying the cyclical nature of the motion shown by the floating plate. The above findings indicate that the dimensions of the continental plates present on the Earth's surface have an impact on both the velocity and duration of their movement. The observation that a plate that is too small stagnates on top of a subduction current, while a plate that is too large stagnates on top of an upwelling current, suggests that the smaller continent of New Zealand is likely to experience a decrease in elevation due to its location above a subduction current. Conversely, the larger continent of Africa is expected to undergo uplift and attain a higher elevation as a result of its position above an upwelling current.

Qualitative behavior in a fractional order IS-LM-AS macroeconomic model with stability analysis

In this article, we analyze the conditions for the structural stability of a fractional order IS-LM-AS dynamic model with adaptive expectations. It is a generalization of our previous research lately published in the literature. We also present the conditions that the structural parameters of the model must meet for the economic system to present a periodic movement when the critical value of the fractional order of the system, q* , guarantees the presence of a Hopf bifurcation of degenerate type. The theoretical analysis is complemented with numerical simulations of the phase portraits in R3 and of the temporal trajectories of the solutions of the model in MATLAB software. Finally, it is important to highlight that unlike the results of our previous research, the qualitative results found in this paper show that all the structural parameters of the model are essential in determining its global asymptotic stability and Hopf bifurcation.

Zero-shot model-free learning of periodic movements for a bio-inspired soft-robotic arm

In recent years, soft robots gain increasing attention as a result of their compliance when operating in unstructured environments, and their flexibility that ensures safety when interacting with humans. However, challenges lie on the difficulty to develop control algorithms due to various limitations induced by their soft structure. In this paper, we introduce a novel technique that aims to perform motion control of a modular bio-inspired soft-robotic arm, with the main focus lying on facilitating the qualitative reproduction of well-specified periodic trajectories. The introduced method combines the notion behind two previously developed methodologies both based on the Movement Primitive (MP) theory, by exploiting their capabilities while coping with their main drawbacks. Concretely, the requested actuation is initially computed using a Probabilistic MP (ProMP)-based method that considers the trajectory as a combination of simple movements previously learned and stored as a MP library. Subsequently, the key components of the resulting actuation are extracted and filtered in the frequency domain. These are eventually used as input to a Central Pattern Generator (CPG)-based model that takes over the generation of rhythmic patterns at the motor level. The proposed methodology is evaluated on a two-module soft arm. Results show that the first algorithmic component (ProMP) provides an immediate estimation of the requested actuation by avoiding time-consuming training, while the latter (CPG) further simplifies the execution by allowing its control through a low-dimensional parameterization. Altogether, these results open new avenues for the rapid acquisition of periodic movements in soft robots, and their compression into CPG parameters for long-term storage and execution.