Information Processing Performance Research Articles

A BP Neural Network-Based Communication Blind Signal Detection Method With Cyber-Physical-Social Systems

The development of wireless communication technologies will lead to an increase of rapid-time-variants featured occasions and physical occasions of small-data-size communication in network, and the modulation system diversification resulting from social group densification. Though traditional blind signal detection approaches have been improved by reducing their excessive reliance on data size, they still have the defects of various postulated conditions in new settings, complicated computation, unstable detection effect and high error rate. This paper aims to explore a communication blind signal detection method in the setting of cyber-physical-social systems in the field of back-propagation (BP) neural network. First, a BP neural network is used as the equalizer, an error function is redefined, and the back-propagation algorithm is used to train and adjust blind signal data deviation and to update network weight rules for adaptation to network settings with rapid time-variants. Second, a double-sigmoid BP neural network excitation function is constructed to improve poor multiple information processing and network performances resulting from social group densification. Third, self-adaptive variable step size for physical devices’ power is constructed to adjust the conflict between convergence rate and steady-state error caused by different powers with the increase of small-data-size communication. Finally, an output vector is made to be closest to an expected vector; thereby, blind signal detection rate of social groups’ communication using physical devices in the cyber environment can be improved. The experiments show that the communication blind signal detection method proposed in the paper improves signal detection precision, and reduces omission rate (below 2%). Besides, the method is characterized by minor error, removes deficiencies of traditional methods for blind signal extraction, and can effectively accomplish blind signal detection.

Effects of Quality and Quantity of Information Processing on Design Coordination Performance

It is acknowledged that lacking of interdisciplinary communication amongst designers can result in poor coordination performance in building design. Viewing communication as information processing activity, this paper aims to explore the relationship between interdisciplinary information processing (IP) and design coordination performance. Both amount and quality are concerned regarding information processing. 698 project based samples are collected by questionnaire survey from design institutes in mainland China. Statistical data analysis shows that the relationship between information processing amount and design coordination performance follows a nonlinear exponential expression: performance = 3.691 (1-0.235IP amount) rather than reverted U curve. It implies that design period is too short to allow information overload. It indicates that the main problem in interdisciplinary communication in design institute in China is insufficient information. In additional, it is found the correlation between IP quality and coordination process performance is much stronger than that between IP amount and coordination process performance. For practitioners, it reminds design mangers to pay more attention to information processing quality rather than amount.

Design of slime-mold-inspired multi-layered single-electron circuit

ABSTRACTWe propose a new single-electron circuit (SEC) that mimics the behaviours of slime molds. The SEC has unique properties and many advantages including extremely low power consumption. However, the most appropriate information processing way on the SEC has not been established yet. As one approach to find the suitable way, we focus on a natural phenomenon, specifically, the behaviours of slime molds. These molds can feed efficiently and their behaviours can be regarded as performing information processing. Their information-processing-like behaviours can be divided into three functions. Therefore, if we can express these functions on the circuit, it can mimic the slime mold behaviour, i.e. it can operate as a slime-mold-inspired information-processing circuit. In this study, we designed a slime-mold-inspired SEC that utilised three functions based on three types of behaviours, and attempted to imitate these functions by using a multi-layered structure. Our circuit has four layers; three for mimicking the divided functions and the last for output. We evaluated its operation by Monte Carlo simulation and confirmed its operation was correct.This paper indicates design of a new single-electron circuit (SEC). For the SEC to process information efficiently, we focus on the behaviors of slime molds. It is known that these molds can feed efficiently and their behaviors can be regarded as performing information processing. In this study, we designed a slime-mold-inspired SEC having a multi-layered structure. We evaluated its operation by Monte Carlo simulation and confirmed its operation was correct. Figure shows a sample operation of our circuit. (a) is the input pattern and (b) is the output pattern, respectively. The optimal path was revealed.

Reservoir Computing Beyond Memory-Nonlinearity Trade-off

Reservoir computing is a brain-inspired machine learning framework that employs a signal-driven dynamical system, in particular harnessing common-signal-induced synchronization which is a widely observed nonlinear phenomenon. Basic understanding of a working principle in reservoir computing can be expected to shed light on how information is stored and processed in nonlinear dynamical systems, potentially leading to progress in a broad range of nonlinear sciences. As a first step toward this goal, from the viewpoint of nonlinear physics and information theory, we study the memory-nonlinearity trade-off uncovered by Dambre et al. (2012). Focusing on a variational equation, we clarify a dynamical mechanism behind the trade-off, which illustrates why nonlinear dynamics degrades memory stored in dynamical system in general. Moreover, based on the trade-off, we propose a mixture reservoir endowed with both linear and nonlinear dynamics and show that it improves the performance of information processing. Interestingly, for some tasks, significant improvements are observed by adding a few linear dynamics to the nonlinear dynamical system. By employing the echo state network model, the effect of the mixture reservoir is numerically verified for a simple function approximation task and for more complex tasks.

Optimal diabatic dynamics of Majorana-based quantum gates

In topological quantum computing, unitary operations on qubits are performed by adiabatic braiding of non-Abelian quasiparticles, such as Majorana zero modes, and are protected from local environmental perturbations. In the adiabatic regime, with timescales set by the inverse gap of the system, the errors can be made arbitrarily small by performing the process more slowly. To enhance the performance of quantum information processing with Majorana zero modes, we apply the theory of optimal control to the diabatic dynamics of Majorana-based qubits. While we sacrifice complete topological protection, we impose constraints on the optimal protocol to take advantage of the nonlocal nature of topological information and increase the robustness of our gates. By using the Pontryagin's maximum principle, we show that robust equivalent gates to perfect adiabatic braiding can be implemented in finite times through optimal pulses. In our implementation, modifications to the device Hamiltonian are avoided. Focusing on thermally isolated systems, we study the effects of calibration errors and external white and $1/f$ (pink) noise on Majorana-based gates. While a noise-induced antiadiabatic behavior, where a slower process creates more diabatic excitations, prohibits indefinite enhancement of the robustness of the adiabatic scheme, our fast optimal protocols exhibit remarkable stability to noise and have the potential to significantly enhance the practical performance of Majorana-based information processing.

Witnessing Irreducible Dimension.

The Hilbert space dimension of a quantum system is the most basic quantifier of its information content. Lower bounds on the dimension can be certified in a device-independent way, based only on observed statistics. We highlight that some such "dimension witnesses" capture only the presence of systems of some dimension, which in a sense is trivial, not the capacity of performing information processing on them, which is the point of experimental efforts to control high-dimensional systems. In order to capture this aspect, we introduce the notion of irreducible dimension of a quantum behavior. This dimension can be certified, and we provide a witness for irreducible dimension four.

The effects of multiple firefighting activities on information processing and work performance in a smoke‐diving room: An intervention study

AbstractFirefighters perform various tasks during firefighting operations under unknown and unpredictable conditions. The present study investigated the impact of firefighting activities and cooling tactics on information processing and work performance. Firefighters performed typical firefighting tasks in the four experimental conditions, namely i) no cooling device (NC), ii) cooling gel (CG), iii) cool vest (CV), and iv) cooling gel and cool vest (CG + CV). The measurement of information processing, Paced Auditory Serial Addition Test (PASAT) scores decreased significantly after the firefighting activities in the four conditions, relative to baseline. The results revealed no significant difference in PASAT scores among the four conditions. However, the performance time (PT) was significantly shorter for the CV and CG + CV compared to the NC and CG conditions. The findings confirmed that the firefighting activities have a detrimental effect on information processing. The CG + CV and CV were more effective than CG and NC in improving PT during firefighting. However, the cooling strategies have a negligible effect on improving information processing performance.

0208 CIRCADIAN MISALIGNMENT IMPACTS ON HUMAN COGNITIVE PERFORMANCE

Shift work increases the risk for disorders of sleep and human error. Overnight operations pose a challenge because our circadian biology promotes nocturnal sleep and daytime vigilance and performance, which may underlie cognitive vulnerability at night. Here we investigated if daily circadian misalignment, typical for night shift work, adversely impacts cognition across diverse cognitive domains. Thirteen healthy young individuals (27.8 ± 9.5 y; 7 men) underwent two 8-day protocols including either 4 days of circadian alignment (day shifts) or misalignment (night shifts; 12-h inverted behavioral/environmental cycles). Cognitive testing included tasks of sustained attention (Psychomotor Vigilance Task; PVT), cognitive throughput (Addition Task; ADD), information processing (Digit Symbol Substitution Task; DSST) visual-spatial performance (Unstable Tracking-Task; TKT) and declarative memory (Probed Recall Memory; PRM), all of which are sensitive to increased sleep pressure and circadian phase. Circadian misalignment over successive days increased cognitive vulnerability by ~10–20% on sustained attention, cognitive throughput, information processing and visual-motor performance, as compared circadian alignment. Attention, as indexed by PVT performance, was acutely impaired during the first 2 days of misalignment with subsequent improvement after 3 days (interaction of “circadian alignment/misalignment”, “day” and “time since awakening”, p=0.006). Conversely, learning, as indexed by changes in ADD, DSST and TKT performance, significantly improved across multiple days of circadian alignment, while no improvement occurred under misalignment (interaction of “circadian alignment/misalignment” and “day”, p<0.05). Lastly, we investigated if the effects of circadian misalignment on performance were also mediated by prior sleep-wake history. Accordingly, lower sleep efficiency in the sleep episode before cognitive testing significantly impaired performance (interaction of “sleep efficiency”, “circadian alignment/misalignment” and “night”; p<0.05). Our data indicate that daily circadian misalignment may explain cognitive vulnerabilities experienced by night workers, and provide a biological framework for the development of countermeasures against adverse cognitive effects in this vulnerable population. National Heart, Lung, and Blood Institute (NHLBI) Grant R01 HL094806, Clinical Translational Science Award UL1RR025758, and Brigham and Women’s Hospital from the National Center for Research Resources.

In patients with major depressive disorders, depression, stress axis activity and problem solving skills as a proxy of executive functions are unrelated

IntroductionMajor depressive disorders (MDD) are among the most prevalent psychiatric disorders worldwide. While there is abundant literature showing that an increased cortisol secretion, understood as a proxy of the deteriorated hypothalamus-pituitary-adrenocortical axis activity (HPA AA), and poor cognitive performance are tightly related, less is known as regards to the HPA AA and higher cognitive information processes such as problem solving.AimsInvestigating the association between cortisol secretion and problem solving performance among patients with MDD.MethodsFifteen inpatients with MDD (HDRS &gt; 24; mean age: 59 years; 80% females) underwent a pharmacologic HPA AA challenge both at baseline and six weeks later to assess the cortisol secretion. They were treated with standard antidepressants at therapeutic dosages. Further, they learned how to solve the Tower-of-Hanoi problem-solving task (ToH-PS-T) and how to apply the problem solving strategy to other tasks (transfer). Testing occurred both at baseline and six weeks later. Outcome variables were symptoms of depression, cortisol secretion and the performance to transfer the acquired ToH-PS-T.ResultsBoth symptoms of depression and cortisol secretion decreased over time, and transfer performance increased over time. Neither at baseline nor six weeks later, symptoms of depression, transfer performance and cortisol secretion were statistically related.ConclusionsThe pattern of results suggests that cortisol secretion as a proxy of physiological stress regulation, symptoms of depression, and higher order cognitive performances seem unrelated. Given that cognitive information processing performance substantively increased regardless from depression and cortisol secretion, problem-solving skills need to be focused separately.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Guest Editorial Special Issue on New Developments in Neural Network Structures for Signal Processing, Autonomous Decision, and Adaptive Control

There has been continuously increasing interest in applying neural networks (NNs) to identification and adaptive control of practical systems that are characterized by nonlinearity, uncertainty, communication constraints, and complexity. The past few years have witnessed a variety of new developments in NN-based approaches for behavior learning, information processing, autonomous decision, and system control. Biologically inspired NN structures can significantly enhance the capabilities of information processing, control, and computational performance. New discoveries in neurocognitive psychology, sociology, and elsewhere reveal new neurological learning structures with more powerful capabilities in complex problem solving and fast decision in dynamic environments. The goal of the special issue is to consolidate recent new developments in NN structures for signal processing, autonomous decision, and adaptive control with application to complex systems. It includes contributions from a wide range of research aspects relevant to the topic, ranging from neural computing, adaptive control, cooperative control, autonomous decision systems, mathematical and computational models, neuropsychology decision and control, algorithms and simulation, to applications and/or case studies. This issue contains 24 papers and the contents of which are summarized below.

The Effect of Various Hot Environments on Physiological Responses and Information Processing Performance Following Firefighting Activities in a Smoke-Diving Room

BackgroundFire service workers often implement multiple duties in the emergency conditions, with such duties being mostly conducted in various ambient temperatures.MethodsThe aim of the current study was to assess the firefighters' physiological responses, information processing, and working memory prior to and following simulated firefighting activities in three different hot environments. Seventeen healthy male firefighters performed simulated firefighting tasks in three separate conditions, namely (1) low heat (LH; 29–31°C, 55–60% relative humidity), (2) moderate heat (MH; 32–34°C, 55–60% relative humidity), and (3) severe heat (SH; 35–37°C, 55–60% relative humidity). It took about 45–50 minutes for each firefighter to finish all defined firefighting activities and the paced auditory serial addition test (PASAT).ResultsAt the end of all the three experimental conditions, heart rate (HR) and tympanic temperature (TT) increased, while PASAT scores as a measure of information processing performance decreased relative to baseline. HR and TT were significantly higher at the end of the experiment in the SH (159.41 ± 4.25 beats/min; 38.22 ± 0.10°C) compared with the MH (156.59 ± 3.77 beats/min; 38.20 ± 0.10°C) and LH (154.24 ± 4.67 beats/min; 38.17 ± 0.10°C) conditions (p < 0.05). There was no significant difference in PASAT scores between LH and MH (p > 0.05). Nonetheless, there was a measurable difference in PASAT scores between LH and SH (p < 0.05).ConclusionThese consequences demonstrate that ambient temperature is effective in raising the physiological responses following firefighting activities. It is therefore argued that further increase of ambient temperature can impact firefighters' information processing and working memory during firefighting activity.

Semantic classification method for network Tibetan corpus

Tibetan web pages appear enormously. It is meaningful that the information processing technology is utilized to find the useful knowledge from the Tibetan web information. Tibetan semantic ontology can enrich the Tibetan digital resource and is helpful to improve the information processing performance. In this paper, semantic classification of Tibetan network corpus is studied. Firstly Tibetan web pages are collected. Secondly preprocessing is conducted to extract the useful information from Web pages. Thirdly the word segmentation and text representation are introduced. Finally the text similarity classification algorithm is proposed to classify the text. During the experiment, the comparison between semantic classification and non semantic classification is conducted. The results show that the semantic classification performance is obviously superior to non semantic classification. This means that making full use of ontology semantic relationship can greatly enhance the classification accuracy. The research is useful and helpful to the study of Tibetan semantic information processing.

Darwin: A neuromorphic hardware co-processor based on spiking neural networks

Abstract Spiking Neural Network (SNN) is a type of biologically-inspired neural networks that perform information processing based on discrete-time spikes, different from traditional Artificial Neural Network (ANN). Hardware implementation of SNNs is necessary for achieving high-performance and low-power. We present the Darwin Neural Processing Unit (NPU), a highly-configurable neuromorphic hardware co-processor based on SNN implemented with digital logic, supporting a configurable number of neurons, synapses and synaptic delays. The Darwin NPU was fabricated by standard 180 nm CMOS technology with area size of 5 × 5 mm2 and 70 MHz clock frequency at the worst case. It consumes 0.84 mW/MHz with 1.8 V power supply for typical applications. Two prototype applications are used to demonstrate the performance and efficiency of the Darwin NPU.

Analysis of EEG Complexity in Patients with Mild Cognitive Impairment

Objective: Mild cognitive impairment patients and normal elderly people were selected in this research. EEG complexity (Lempel-Ziv Complexity, LZC) and P300 value of the two groups were compared in two statuses (quiet eyes closed, cognitive load), The brain functional characteristics of different cognitive states were explored, it was expected to construct a simple and objective cognitive function evaluation approach to provide criteria for early diagnosis of cognitive dysfunction and disease evaluation. Methods: The clinical data was from 50 MCI patients in Neurology department of the 8th People’s Hospital. 45 normal elderly people with corresponding sex, age and education level was chosen as control group. 5 minutes EEG signals were recorded and measured with P300 for both groups with quiet eyes closed and cognitive load states. Due to smooth baseline and inconspicuous artifacts, 2048-point EEG (about 8s) were selected to perform LZC analysis and complexity calculation in Mat tab. Results: 1. Normal elderly people showed higher LZC than MCI patients. Moreover, LZC was higher in those complex brain function areas such as temporal and frontal areas. 2. With the reduction of cognitive function, the value of EEG complexity was reduced accordingly. 3. The cognitive related brain areas showed more obvious degradation than other brain areas. 4. Under the cognitive load status, the complexity value in cognitive related brain areas of MCI patients decreased significantly. 5. The prolongation of P300 latency and LZC decrease of the MCI patients indicated that LZC could reflect the decrease of cognitive function. Discussion: In this study, P300 latencies of MCI group was delayed, we could deduce that because of the decline in brain function and brain areas of fibers connecting, the reduction in information processing performance could indicate that the delay of P300 latent period. These were identical with another study where the complexity of EEG is testified that. Based on these, we could infer, from the perspective of nonlinearity, EEG complexity reveals the changes of brain function in patients with cognitive impairment. Conclusion: The brain electrical LZC value in normal elderly people group was higher than that in cognitive impairment group, those brain areas with more complex functions like frontal area and temporal area had highest LZC, which illustrated the degree distribution differences in complex brain regions. The prolonged latency of P300, these results of cognitive impairment in patients could also predict the degree of cognitive decline.

Convergence Analysis of Inverse Iterative Neural Networks with L2 Penalty

Abstract The iterative inversion of neural networks has been used in solving problems of adaptive control due to its good performance of information processing. In this paper an iterative inversion neural network with L2 penalty term has been presented trained by using the classical gradient descent method. We mainly focus on the theoretical analysis of this proposed algorithm such as monotonicity of error function, boundedness of input sequences and weak (strong) convergence behavior. For bounded property of inputs, we rigorously proved that the feasible solutions of input are restricted in a measurable field. The weak convergence means that the gradient of error function with respect to input tends to zero as the iterations go to infinity while the strong convergence stands for the iterative sequence of input vectors convergence to a fixed optimal point.

Randomized controlled trial of a web-based multi-modal therapy program for executive functioning in children and adolescents with unilateral cerebral palsy

Purpose state: Determine the efficacy of Move-it-to-improve-it (Mitii™), a multi-modal web-based program, in improving Executive Function (EF) in children with unilateral cerebral palsy (UCP).Method: Participants (n = 102) were matched in pairs then randomized to: intervention (Mitii™ for 20 weeks; n = 51; 26 males; mean age = 11 years 8 months (SD = 2 years 4 months); Full Scale IQ = 84.65 (SD = 15.19); 28 left UCP; GMFCS-E&R (I = 20, II = 31) or waitlist control (n = 50; 25 males; mean age = 11 years 10 months (SD = 2 years 5 months); Full Scale IQ = 80.75 (SD = 19.81); 20 left UCP; GMFCS-E&R (I = 25, II = 25). Mitii™ targeted working memory (WM), visual processing (VP), upper limb co-ordination and physical activity. EF capacity was assessed: attentional control (DSB; WISC-IV); cognitive flexibility (inhibition and number-letter sequencing DKEFS); goal setting (D-KEFs Tower Test); and information processing (WISC-IV Symbol Search and Coding). EF performance was assessed via parent report (BRIEF). Groups were compared at 20 weeks using linear regression (SPSS 21).Results: There were no significant between group differences in attentional control (DSB; p = 0.20;CI= −0.40,1.87); cognitive flexibility (Inhibition, p = 0.34; CI= −0.73,2.11; number/letter sequencing, p = 0.17; CI= −0.55,2.94); problem solving (Tower; p = 0.28; CI= −0.61,2.09), information processing (Symbol; p = 0.08; CI= −0.16, 2.75; Coding; p = 0.07; CI= −0.12,2.52) or EF performance (p = 0.13; CI= −10.04,1.38).Conclusion:In a large RCT, MitiiTM did not lead to significant improvements on measures of EF or parent ratings of EF performance in children with UCP.Implications for rehabilitationA large RCT of the multi-modal web based training; Move It to Improve It (MitiiTM) improves motor processing, visual perception, and physical capacity but does demonstrate statistically significant improvements or clinical significance in executive function in children with mild to moderate unilateral cerebral palsy (UCP).MitiiTM training completed by an intervention group was highly variable with few children reaching the target dosage of 60 h. Technical issues including server and internet connectively problems lead to disengagement with the program.Web-based training delivered in the home has the potential to increase therapy dose and accessibility, however, MitiiTM needs to be tailored to include tasks involving goal-setting, more complex problem solving using multi-dimensional strategies, mental flexibility, switching between two cognitively demanding tasks, and greater novelty in order to increase the cognitive component and challenge required to drive changes in EF.

Cognitive control network anatomy correlates with neurocognitive behavior: A longitudinal study

Cognitive control is the process of employing executive functions, such as attention, planning or working memory, to guide appropriate behaviors in order to achieve a specific goal. Functional magnetic resonance imaging studies suggest a superordinate cognitive control network, comprising the dorsal regions of the lateral prefrontal cortex (DLPFC), anterior cingulate cortex (dACC) and parietal cortex (DPC). How gray matter structure changes across this network throughout neurodevelopment and how these changes impact cognitive control are not yet fully understood. Here we investigate changes in gray matter volume of the key nodes of the cognitive control network using structural MRI scans from 176 participants aged 8–38 years. One hundred and eleven of these also completed a longitudinal follow‐up at two years. We compare these with performance on a cognitive battery also measured at these two time points. We found that volume decreases in the cognitive control network were associated with improved performance in executive function (in left DLPFC and bilateral DPC), information processing (in bilateral dACC and right DPC) and emotion identification tasks (left DLPFC). These results were significant after controlling for age. Furthermore, gray matter changes were coordinated across the network. These findings imply age‐independent synaptic pruning in the cognitive control network may have a role in improving performance in cognitive domains. This study provides insight into the direct impact of structural changes on behavior within this network during neurodevelopment and provides a normative evidence base to better understand development of cognitive dysfunction in brain disorders. Hum Brain Mapp 38:631–643, 2017. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Environmental Performance and Analyst Information Processing Costs

This study tests the hypothesis that analyst information processing costs vary positively in the level of firms’ environmental performance ratings. Based on proxies for analyst information processing costs (e.g., the number of stocks followed, frequency and timeliness of earnings revisions, the accuracy of earnings forecasts), we find results to support this hypothesis. These findings deepen our knowledge of the informational setting that conditions analysts’ decisions by identifying the cost of processing environmental information as a potential determinant of the stocks analysts include in their portfolios. Our findings also have implications for capital market efficiency because the higher information processing costs induced by environmental performance ratings could discourage analysts from developing trading strategies to exploit asset mispricing.

Spatial compatibility and affordance compatibility in patients with chronic schizophrenia.

A deterioration in information-processing performance is commonly recognized in patients with chronic schizophrenia. Although the enhancement of cognitive skills in patients with schizophrenia is important, the types of external stimuli that influence performance have not received much attention. The aim of present study was to clarify the effects of spatial and affordance compatibility in patients with schizophrenia, compared with those in healthy people. The subjects (25 patients with schizophrenia and 25 healthy controls) participated in two experiment examining the effects of the spatial location of stimuli and the action-relevance of objects. The results showed that the effect of spatial compatibility was similar in both the patients and the controls, whereas the influence of action-relevant objects was not highlighted in either patients with chronic schizophrenia or healthy controls. These findings provide important evidence of a normal spatial compatibility effect in patients with chronic schizophrenia. However, further research examining the affordance compatibility effect is needed, taking into consideration the symptomatology and the severity of the social functioning level in patients with schizophrenia.

Muscle, functional and cognitive adaptations after flywheel resistance training in stroke patients: a pilot randomized controlled trial.

BackgroundResistance exercise (RE) improves neuromuscular function and physical performance after stroke. Yet, the effects of RE emphasizing eccentric (ECC; lengthening) actions on muscle hypertrophy and cognitive function in stroke patients are currently unknown. Thus, this study explored the effects of ECC-overload RE training on skeletal muscle size and function, and cognitive performance in individuals with stroke.MethodsThirty-two individuals with chronic stroke (≥6 months post-stroke) were randomly assigned into a training group (TG; n = 16) performing ECC-overload flywheel RE of the more-affected lower limb (12 weeks, 2 times/week; 4 sets of 7 maximal closed-chain knee extensions; <2 min of contractile activity per session) or a control group (CG; n = 16), maintaining daily routines. Before and after the intervention, quadriceps femoris volume, maximal force and power for each leg were assessed, and functional and dual task performance, and cognitive functions were measured.ResultsQuadriceps femoris volume of the more-affected leg increased by 9.4 % in TG. Muscle power of the more-affected, trained (48.2 %), and the less-affected, untrained limb (28.1 %) increased after training. TG showed enhanced balance (8.9 %), gait performance (10.6 %), dual-task performance, executive functions (working memory, verbal fluency tasks), attention, and speed of information processing. CG showed no changes.ConclusionECC-overload flywheel resistance exercise comprising 4 min of contractile activity per week offers a powerful aid to regain muscle mass and function, and functional performance in individuals with stroke. While the current intervention improved cognitive functions, the cause-effect relationship, if any, with the concomitant neuromuscular adaptations remains to be explored.Trial registrationClinical Trials NCT02120846