scholarly journals Correlating Grip Force Signals from Multiple Sensors Highlights Prehensile Control Strategies in a Complex Task-User System

2020 ◽  
Vol 7 (4) ◽  
pp. 143
Author(s):  
Birgitta Dresp-Langley ◽  
Florent Nageotte ◽  
Philippe Zanne ◽  
Michel de Mathelin
Keyword(s):  
Real Time ◽  
Force Control ◽  
Grip Force ◽  
Control Strategies ◽  
Sensor Data ◽  
Dominant Hand ◽  
Complex Task ◽  
The Individual ◽  
Receptive Field Organization ◽  
Force Profiles

Wearable sensor systems with transmitting capabilities are currently employed for the biometric screening of exercise activities and other performance data. Such technology is generally wireless and enables the non-invasive monitoring of signals to track and trace user behaviors in real time. Examples include signals relative to hand and finger movements or force control reflected by individual grip force data. As will be shown here, these signals directly translate into task, skill, and hand-specific (dominant versus non-dominant hand) grip force profiles for different measurement loci in the fingers and palm of the hand. The present study draws from thousands of such sensor data recorded from multiple spatial locations. The individual grip force profiles of a highly proficient left-hander (expert), a right-handed dominant-hand-trained user, and a right-handed novice performing an image-guided, robot-assisted precision task with the dominant or the non-dominant hand are analyzed. The step-by-step statistical approach follows Tukey’s “detective work” principle, guided by explicit functional assumptions relating to somatosensory receptive field organization in the human brain. Correlation analyses (Person’s product moment) reveal skill-specific differences in co-variation patterns in the individual grip force profiles. These can be functionally mapped to from-global-to-local coding principles in the brain networks that govern grip force control and its optimization with a specific task expertise. Implications for the real-time monitoring of grip forces and performance training in complex task-user systems are brought forward.

scholarly journals Correlating Grip Force Signals From Multiple Sensors Highlights Functional Synergies of Manual Control in a Complex Task-User System

2020 ◽  
Author(s):  
Birgitta Dresp-Langley ◽  
Florent Nageotte ◽  
Philippe Zanne ◽  
Michel de Mathelin
Keyword(s):  
Real Time ◽  
Grip Force ◽  
Pressure Control ◽  
Sensor Data ◽  
Dominant Hand ◽  
Complex Task ◽  
Multiple Sources ◽  
Multiple Sensors ◽  
Palm Of The Hand ◽  
Force Profiles

Biosensors and wearable sensor systems with transmitting capabilities are currently developed and used for the monitoring of health data, exercise activities, and other performance data. Unlike conventional approaches, these devices enable convenient, continuous, and unobtrusive monitoring of a user’s behavioral signals in real time. Examples include signals relative to hand an finger movement/pressure control reflected by individual grip force data. As will be shown here, these directly translate into task, skill and hand-specific (dominant versus non-dominant hand) grip force profiles for different measurement loci in the fingers and palm of the hand. On the basis of thousands of sensor data from multiple sensor locations, individual grip force profiles of an task expert, a trained user and a highly proficient user (expert) performing an image-guided and robot-assisted precision task with the dominant or the non-dominant hand are analyzed in several steps following Tukey’s “detective work” approach. Correlation analyses (Person’s Product Moment) reveal skill-specific differences in individual grip force profiles across multiple sources of variation, functionally mapped to the somatosensory brain networks which ensure grip force control and its evolution with control expertise. Implications for the real-time monitoring of individual grip force profiles and their evolution with training in complex task-user systems are brought forward.

scholarly journals Making Sense of Complex Sensor Data Streams

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1391
Author(s):  
Rongrong Liu ◽  
Birgitta Dresp-Langley
Keyword(s):  
Data Analysis ◽  
Grip Force ◽  
Human Performance ◽  
Precision Grip ◽  
Individual Variability ◽  
Sensor Data ◽  
Dominant Hand ◽  
Analysis Strategies ◽  
The Individual ◽  
Force Profiles

This concept paper draws from our previous research on individual grip force data collected from biosensors placed on specific anatomical locations in the dominant and non-dominant hand of operators performing a robot-assisted precision grip task for minimally invasive endoscopic surgery. The specificity of the robotic system on the one hand, and that of the 2D image-guided task performed in a real-world 3D space on the other, constrain the individual hand and finger movements during task performance in a unique way. Our previous work showed task-specific characteristics of operator expertise in terms of specific grip force profiles, which we were able to detect in thousands of highly variable individual data. This concept paper is focused on two complementary data analysis strategies that allow achieving such a goal. In contrast with other sensor data analysis strategies aimed at minimizing variance in the data, it is necessary to decipher the meaning of intra- and inter-individual variance in the sensor data on the basis of appropriate statistical analyses, as shown in the first part of this paper. Then, it is explained how the computation of individual spatio-temporal grip force profiles allows detecting expertise-specific differences between individual users. It is concluded that both analytic strategies are complementary and enable drawing meaning from thousands of biosensor data reflecting human performance measures while fully taking into account their considerable inter- and intra-individual variability.

scholarly journals Wearable Wireless Biosensors for Spatiotemporal Grip Force Profiling in Real Time

2020 ◽  
Vol 2 (1) ◽  
pp. 45
Author(s):  
Rongrong Liu ◽  
Florent Nageotte ◽  
Philippe Zanne ◽  
Michel de Mathelin ◽  
Birgitta Dresp-Langley
Keyword(s):  
Real Time ◽  
Grip Force ◽  
Behavioral Science ◽  
Middle Finger ◽  
Sensor Data ◽  
Dominant Hand ◽  
Biologically Inspired ◽  
Systems Neuroscience ◽  
Spatio Temporal ◽  
Force Profiles

The temporal evolution of individual grip force profiles of a novice using a robotic system for minimally invasive endoscopic surgery is analyzed on the basis of thousands of individual sensor data recorded in real time through a wearable wireless sensor glove system. The spatio-temporal grip force profiles from specific sensor locations in the dominant hand performing a four-step pick-and-drop simulator task reveal skill-relevant differences in force deployment by the small finger (fine grip force control) and the middle finger (gross grip force contribution) by comparison with the profiles of a highly proficient expert. Cross-disciplinary insights from systems neuroscience, cognitive behavioral science, and robotics, with implications for biologically inspired AI for human–robot interactions, highlight the functional significance of spatio-temporal grip force profiling.

scholarly journals Neural Correlates of Age-Related Changes in Precise Grip Force Regulation: A Combined EEG-fNIRS Study

2020 ◽  
Vol 12 ◽  
Author(s):  
Alisa Berger ◽  
Fabian Steinberg ◽  
Fabian Thomas ◽  
Michael Doppelmayr
Keyword(s):  
Older Adults ◽  
Motor Control ◽  
Force Control ◽  
Grip Force ◽  
Task Complexity ◽  
Brain Activity ◽  
Dominant Hand ◽  
Grip Force Control ◽  
Age Related ◽  
Age Related Changes

Motor control is associated with suppression of oscillatory activity in alpha (8–12 Hz) and beta (12–30 Hz) ranges and elevation of oxygenated hemoglobin levels in motor-cortical areas. Aging leads to changes in oscillatory and hemodynamic brain activity and impairments in motor control. However, the relationship between age-related changes in motor control and brain activity is not yet fully understood. Therefore, this study aimed to investigate age-related and task-complexity-related changes in grip force control and the underlying oscillatory and hemodynamic activity. Sixteen younger [age (mean ± SD) = 25.4 ± 1.9, 20–30 years] and 16 older (age = 56.7 ± 4.7, 50–70 years) healthy men were asked to use a power grip to perform six trials each of easy and complex force tracking tasks (FTTs) with their right dominant hand in a randomized within-subject design. Grip force control was assessed using a sensor-based device. Brain activity in premotor and primary motor areas of both hemispheres was assessed by electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Older adults showed significantly higher inaccuracies and higher hemodynamic activity in both FTTs than did young adults. Correlations between grip force control owing to task complexity and beta activity were different in the contralateral premotor cortex (PMC) between younger and older adults. Collectively, these findings suggest that aging leads to impairment of grip force control and an increase in hemodynamic activity independent of task complexity. EEG beta oscillations may represent a task-specific neurophysiological marker for age-related decline in complex grip force control and its underlying compensation strategies. Further EEG-fNIRS studies are necessary to determine neurophysiological markers of dysfunctions underlying age-related motor disabilities for the improvement of individual diagnosis and therapeutic approaches.

Real-time Friction Estimation for Grip Force Control

2021 ◽  
Author(s):  
Heba Khamis ◽  
Benjamin Xia ◽  
Stephen J. Redmond
Keyword(s):  
Real Time ◽  
Force Control ◽  
Grip Force ◽  
Grip Force Control ◽  
Friction Estimation

scholarly journals Real-time slacking as a default mode of grip force control: implications for force minimization and personal grip force variation

2018 ◽  
Vol 120 (4) ◽  
pp. 2107-2120 ◽  
Author(s):  
Brendan W. Smith ◽  
Justin B. Rowe ◽  
David J. Reinkensmeyer
Keyword(s):  
Real Time ◽  
Force Control ◽  
Motor System ◽  
Grip Force ◽  
Maximum Voluntary Contraction ◽  
Force Production ◽  
Arm Movement ◽  
Voluntary Contraction ◽  
Grip Force Control ◽  
Force Variation

During trial-to-trial movement adaptation, the motor system systematically reduces extraneous muscle forces when kinematic errors experienced on previous movements are small, a phenomenon termed “slacking.” There is also growing evidence that the motor system slacks continuously (i.e., in real-time) during arm movement or grip force control, but the initiation of this slacking is not well-characterized, obfuscating its physiological cause. Here, we addressed this issue by asking participants ( n = 32) to track discrete force targets presented visually using isometric grip force, then applying a brief, subtle error-clamp to that visual feedback on random trials. Participants reduced their force in an exponential fashion, on these error-clamp trials, except when the target force was <10% maximum voluntary contraction (MVC). This force drift began <250 ms after the onset of the error-clamp, consistent with slacking being an ongoing process unmasked immediately after the motor system finished reacting to the last veridical feedback. Above 10% MVC, the slacking rate increased linearly with grip force magnitude. Grip force variation was approximately 50–100% higher with veridical feedback, largely due to heightened signal power at ~1 Hz, the band of visuomotor feedback control. Finally, the slacking rate measured for each participant during error-clamp trials correlated with their force variation during control trials. That is, participants who slacked more had greater force variation. These results suggest that real-time slacking continuously reduces grip force until visual error prompts correction. Whereas such slacking is suited for force minimization, it may also account for ~30% of the variability in personal grip force variation.NEW & NOTEWORTHY We provide evidence that a form of slacking continuously conditions real-time grip force production. This slacking is well-suited to promote efficiency but is expected to increase force variation by triggering additional feedback corrections. Moreover, we show that the rate at which a person slacks is substantially correlated with the variation of their grip force. In combination, at the neurophysiological level, our results suggest slacking is caused by one or more relatively smooth neural adaptations.

Pollution based real time control strategies for combined sewer systems

1997 ◽  
Vol 36 (8-9) ◽  
pp. 331-336 ◽  
Author(s):  
Gabriela Weinreich ◽  
Wolfgang Schilling ◽  
Ane Birkely ◽  
Tallak Moland
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Ammonia Nitrogen ◽  
Simple Extension ◽  
Real Time Control ◽  
Time Control ◽  
Sewer Systems ◽  
Receiving Waters ◽  
Tunnel System

This paper presents results from an application of a newly developed simulation tool for pollution based real time control (PBRTC) of urban drainage systems. The Oslo interceptor tunnel is used as a case study. The paper focuses on the reduction of total phosphorus Ptot and ammonia-nitrogen NH4-N overflow loads into the receiving waters by means of optimized operation of the tunnel system. With PBRTC the total reduction of the Ptot load is 48% and of the NH4-N load 51%. Compared to the volume based RTC scenario the reductions are 11% and 15%, respectively. These further reductions could be achieved with a relatively simple extension of the operation strategy.

scholarly journals Power Hardware-in-the-Loop-Based Performance Analysis of Different Converter Controllers for Fast Active Power Regulation in Low-Inertia Power Systems

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3274
Author(s):  
Jose Rueda Torres ◽  
Zameer Ahmad ◽  
Nidarshan Veera Kumar ◽  
Elyas Rakhshani ◽  
Ebrahim Adabi ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Power Systems ◽  
Real Time ◽  
Control Strategies ◽  
Active Power ◽  
Power Electronic ◽  
Hardware In The Loop ◽  
Digital Controllers ◽  
Power Regulation ◽  
The Impact

Future electrical power systems will be dominated by power electronic converters, which are deployed for the integration of renewable power plants, responsive demand, and different types of storage systems. The stability of such systems will strongly depend on the control strategies attached to the converters. In this context, laboratory-scale setups are becoming the key tools for prototyping and evaluating the performance and robustness of different converter technologies and control strategies. The performance evaluation of control strategies for dynamic frequency support using fast active power regulation (FAPR) requires the urgent development of a suitable power hardware-in-the-loop (PHIL) setup. In this paper, the most prominent emerging types of FAPR are selected and studied: droop-based FAPR, droop derivative-based FAPR, and virtual synchronous power (VSP)-based FAPR. A novel setup for PHIL-based performance evaluation of these strategies is proposed. The setup combines the advanced modeling and simulation functions of a real-time digital simulation platform (RTDS), an external programmable unit to implement the studied FAPR control strategies as digital controllers, and actual hardware. The hardware setup consists of a grid emulator to recreate the dynamic response as seen from the interface bus of the grid side converter of a power electronic-interfaced device (e.g., type-IV wind turbines), and a mockup voltage source converter (VSC, i.e., a device under test (DUT)). The DUT is virtually interfaced to one high-voltage bus of the electromagnetic transient (EMT) representation of a variant of the IEEE 9 bus test system, which has been modified to consider an operating condition with 52% of the total supply provided by wind power generation. The selected and programmed FAPR strategies are applied to the DUT, with the ultimate goal of ascertaining its feasibility and effectiveness with respect to the pure software-based EMT representation performed in real time. Particularly, the time-varying response of the active power injection by each FAPR control strategy and the impact on the instantaneous frequency excursions occurring in the frequency containment periods are analyzed. The performed tests show the degree of improvements on both the rate-of-change-of-frequency (RoCoF) and the maximum frequency excursion (e.g., nadir).

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