Oscillometric blood pressure measurements on smartphones using vibrometric force estimation.

This paper proposes a smartphone-based method for measuring Blood Pressure (BP) using the oscillometric method. For oscillometry, it is necessary to measure (1) the pressure applied to the artery and (2) the local blood volume change. This is accomplished by performing an oscillometric measurement at the finger's digital artery, whereby a user presses down on the phone's camera with steadily increasing force. The camera is used to capture the blood volume change using photoplethysmography. We devised a novel method for measuring the force applied of the finger without the use of specialized smartphone hardware with a technique called Vibrometric Force Estimation (VFE). The fundamental concept of VFE relies on a phenomenon where a vibrating object is dampened when an external force is applied on to it. This phenomenon can be recreated using the phone's own vibration motor and measured using the phone's Inertial Measurement Unit (IMU). A cross device reliability study with three smartphones of different manufacturers, shape, and prices results in similar force estimation performance across all smartphone models. In an N = 24 proof of concept study of the BP measurement, the smartphone technique achieves a mean absolute error of 9.21 mmHg and 7.77 mmHg of systolic and diastolic BP, respectively, compared to an FDA approved BP cuff. The vision for this technology is not necessarily to replace existing BP monitoring solutions, but rather to introduce a downloadable smartphone software application that could serve as a low-barrier hypertension screening measurement fit for widespread adoption.

Simultaneous Estimation of Digit Tip Forces and Hand Postures in a Simulated Real-Life Condition With High-Density Electromyography and Deep Learning.

In myoelectric control, continuous estimation of multiple degrees of freedom has an important role. Most studies have focused on estimating discrete postures or forces of the human hand but for a practical prosthetic system, both should be considered. In daily life activities, hand postures vary for grasping different objects and the amount of force exerted on each fingertip depends on the shape and weight of the object. This study aims to investigate the feasibility of continuous estimation of multiple degrees of freedom. We proposed a reach and grasp framework to study both absolute fingertip forces and hand movement types using deep learning techniques applied to high-density surface electromyography (HD-sEMG). Four daily life grasp types were examined and absolute fingertip forces were simultaneously estimated while grasping various objects, along with the grasp types. We showed that combining a 3-dimensional Convolutional Neural Network (3DCNN) with a Long Short-term Memory (LSTM) can reliably and continuously estimate the digit tip forces and classify different hand postures in human individuals. The mean absolute error (MAE) and Pearson correlation coefficient (PCC) results of the force estimation problem across all fingers and subjects were 0.46 ± 0.23 and 0.90 ± 0.03% respectively and for the classification problem, they were 0.04 ± 0.01 and 0.97 ± 0.02%. The results demonstrated that both absolute digit tip forces and hand postures can be successfully estimated through deep learning and HD-sEMG.

Dual-ratio approach to pulse oximetry and the effect of skin tone.

Significance: Pulsatile blood oxygen saturation ( SpO 2 ) via pulse oximetry is a valuable clinical metric for assessing oxygen delivery. Individual anatomical features, including skin tone, may affect current optical pulse oximetry methods. Aim: We developed an optical pulse oximetry method based on dual-ratio (DR) measurements to suppress individual anatomical confounds on SpO 2 . Approach: We designed a DR-based finger pulse oximeter, hypothesizing that DR would suppress confounds from optical coupling and superficial tissue absorption. This method is tested using Monte Carlo simulations and in vivo experiments. Results: Different melanosome volume fractions in the epidermis, a surrogate for skin tone, cause changes in the recovered SpO 2 on the order of 1% in simulation and in vivo. Different heterogeneous pulsatile hemodynamics cause greater changes on the order of 10% in simulations. SpO 2 recovered with DR measurements showed less variability than the traditional single-distance (SD) transmission method. Conclusions: For the models and methods considered here, SpO 2 measurements are strongly impacted by heterogeneous pulsatile hemodynamics. This variability may be larger than the skin tone bias, which is a known confound in SpO 2 measurements. The partial suppression of variability in the SpO 2 recovered by DR suggests the promise of DR for pulse oximetry.

Enhancing smartphone security with human centric bimodal fallback authentication leveraging sensors.

Smartphones store valuable personal information, necessitating robust authentication methods to protect user data. This research proposes a lightweight bi-model fallback authentication technique that combines dynamic security questions and finger pattern recognition using inertial measurement units. The dynamic security questions are generated based on the smartphone's usage behavior, while the owner's finger movements are captured using four different inertial sensors: accelerometer, gyroscope, gravity sensor, and magnetometer. By combining the answers to the questions and the owner's finger movements, the user can be authenticated even if the primary authentication method fails. In this study, data was collected from 24 participants, including 12 primary phone users and 12 close adversaries, over a span of 28 days. The dynamic security questions, derived from call, SMS, battery charging events, application usage, location, and physical activity categories, achieved high accuracy rates, with call, SMS, and application usage surpassing 90 % . Incorporating the inertial measurement units significantly improved the accuracy of all question types, increasing from a maximum of 76 % to 90.99 % , while also enhancing the True Positive Rate from 0.79 to 0.99 compared to a previous study. This research presents a promising lightweight bi-model fallback authentication technique that leverages dynamic security questions and inertial measurement units data, demonstrating its effectiveness for enhancing smartphone security.

Tactile stimulation designs adapted to clinical settings result in reliable fMRI-based somatosensory digit maps.

Movement constraints in stroke survivors are often accompanied by additional impairments in related somatosensory perception. A complex interplay between the primary somatosensory and motor cortices is essential for adequate and precise movements. This necessitates investigating the role of the primary somatosensory cortex in movement deficits of stroke survivors. The first step towards this goal could be a fast and reliable functional Magnetic Resonance Imaging (fMRI)-based mapping of the somatosensory cortex applicable for clinical settings. Here, we compare two 3 T fMRI-based somatosensory digit mapping techniques adapted for clinical usage in seven neurotypical volunteers and two sessions, to assess their validity and retest-reliability. Both, the traveling wave and the blocked design approach resulted in complete digit maps in both sessions of all participants, showing the expected layout. Similarly, no evidence for differences in the volume of activation, nor the activation overlap between neighboring activations could be detected, indicating the general feasibility of the clinical adaptation and their validity. Retest-reliability, indicated by the Dice coefficient, exhibited reasonable values for the spatial correspondence of single digit activations across sessions, but low values for the spatial correspondence of the area of overlap between neighboring digits across sessions. Parameters describing the location of the single digit activations exhibited very high correlations across sessions, while activation volume and overlap only exhibited medium to low correlations. The feasibility and high retest-reliabilities for the parameters describing the location of the single digit activations are promising concerning the implementation into a clinical context to supplement diagnosis and treatment stratification in upper limb stroke patients.

How to Make the Skin Contact Area Controllable by Optical Calibration in Wearable Tactile Displays of Softness.

Virtual reality systems may benefit from wearable (fingertip-mounted) haptic displays capable of rendering the softness of virtual objects. According to neurophysiological evidence, the easiest reliable way to render a virtual softness is to generate purely tactile (as opposed to kinaesthetic) feedback to be delivered via a finger-pulp-interfaced deformable surface. Moreover, it is necessary to control not only the skin indentation depth by applying quasi-static (non-vibratory) contact pressures, but also the skin contact area. This is typically impossible with available devices, even with those that can vary the contact area, because the latter cannot be controlled due to the complexity of sensing it at high resolutions. This causes indetermination on an important tactile cue to render softness. Here, we present a technology that allows the contact area to be open-loop controlled via personalised optical calibrations. We demonstrate the solution on a modified, pneumatic wearable tactile display of softness previously described by us, consisting of a small chamber containing a transparent membrane inflated against the finger pulp. A window on the device allowed for monitoring the skin contact area with a camera from an external unit to generate a calibration curve by processing photos of the skin membrane interface at different pressures. The solution was validated by comparisons with an ink-stain-based method. Moreover, to avoid manual calibrations, a preliminary automated procedure was developed. This calibration strategy may be applied also to other kinds of displays where finger pulps are in contact with transparent deformable structures.

Investigating the role of auditory cues in modulating motor timing: insights from EEG and deep learning.

Research on action-based timing has shed light on the temporal dynamics of sensorimotor coordination. This study investigates the neural mechanisms underlying action-based timing, particularly during finger-tapping tasks involving synchronized and syncopated patterns. Twelve healthy participants completed a continuation task, alternating between tapping in time with an auditory metronome (pacing) and continuing without it (continuation). Electroencephalography data were collected to explore how neural activity changes across these coordination modes and phases. We applied deep learning methods to classify single-trial electroencephalography data and predict behavioral timing conditions. Results showed significant classification accuracy for distinguishing between pacing and continuation phases, particularly during the presence of auditory cues, emphasizing the role of auditory input in motor timing. However, when auditory components were removed from the electroencephalography data, the differentiation between phases became inconclusive. Mean accuracy asynchrony, a measure of timing error, emerged as a superior predictor of performance variability compared to inter-response interval. These findings highlight the importance of auditory cues in modulating motor timing behaviors and present the challenges of isolating motor activation in the absence of auditory stimuli. Our study offers new insights into the neural dynamics of motor timing and demonstrates the utility of deep learning in analyzing single-trial electroencephalography data.

Task demands modulate distal limb handedness: A comparative analysis of prehensile synergies of the dominant and non-dominant hand.

The dynamic dominance hypothesis of handedness suggests a distinct control strategy for the dominant and the non-dominant limb. The hypothesis demonstrated that the dominant proximal limb is tuned for optimal trajectory control while the non-dominant limb is tuned for a stable grasp. Whether the hypothesis can be extended to distal segments like fingers, especially during a five-fingered grasp, has been studied little. To examine this, an attempt was made to compare the prehensile synergies and force magnitudes of the dominant (DOM) and non-dominant hands (NDOM) during a 5-fingered prehension task. Participants traced a trapezoidal and inverse trapezoidal path with their thumbs on a sliding platform while holding a handle in static equilibrium. The DOM hand performed better only in the inverse trapezoid condition, exhibiting a reduced grip force and increased synergy index aligning with the dynamic dominance hypothesis. No differences were observed for the trapezoid condition, likely due to reduced task demands. The study also explored changes in anticipatory synergy adjustments between the DOM and NDOM hands, but the differences were non-significant. Overall, the DOM hand demonstrated better force coordination than the NDOM hand in challenging conditions. Applications of the study in the objective assessment of handedness were proposed.

Cost and benefit of parafoveal information during reading acquisition as revealed by finger movement patterns.

Contrary to expert readers, children learning to read have limited ability to preprocess letters in parafoveal vision. Parafoveal letters induce crowding cost: the features of neighboring letters interfere with target letter identification. We longitudinally studied the weight of parafoveal cost and benefit in two group of children (N = 42), during their first school year (Group 1) and at the end of second school year (Groupe 2). Using a novel digit-tracking method, a blurred text was presented and rendered unblurred by touching the screen, allowing the user to discover a window of visible text as the finger moved along it. We compared two conditions: (1) a large window, where crowding was enhanced by the presence of parafoveal information; (2) a small window, where crowding was suppressed by blurred parafoveal information. Finger kinematics were simultaneously recorded. We found that at the beginning of first-grade, digital fixations - brief slowing or stopping of the finger on a specific point - are significantly longer in the large compared to the small window condition, as parafoveal crowding increases text processing difficulty. This effect diminishes and disappears at the end of second-grade as reading performance improves. In the large window condition, longer digital saccades - rapid movements of the finger changing position - appear by the end of first grade suggesting that parafoveal exposure become more beneficial than harmful when children acquire basic reading skills. Our results show that in beginning readers, crowding has a cognitive cost that interfere with the speed of the learning reading process. Our findings are relevant to the field of education by showing that visual crowding in first grade should not be underestimated.

Effect of Knife Use and Overlapping Gloves on Finger Temperature of Poultry Slaughterhouse Workers.

Brazilian poultry slaughterhouses employ many workers, consequently exposing them to various ergonomic risks. This study aimed to analyze the effects of knife use and overlapping gloves on the finger temperatures of poultry slaughterhouse workers. Employees (n = 571) from seven Brazilian poultry slaughterhouses participated in this cross-sectional study. A Flir® T450SC infrared camera was used to record thermographic images of the workers' hands. The workers were interviewed about work organization, cold thermal sensations, and the perception of upper-limb musculoskeletal discomfort. Dependent and independent sample t-tests and binary logistic regression models were applied. The results proved that the workers wore up to five overlapping gloves and had at least one finger with temperatures of ≤15 °C (46.6%) or ≤24 °C (98.1%). Workers that used a knife and wore a chainmail (CM) glove on their non-dominant hand had average finger temperatures significantly colder on the palmar surface than the anti-cut (AC) glove group (p = 0.029). The chance of one worker who wore a CM glove to have finger temperatures of ≤15 °C was 2.26 times greater than a worker who wore an AC glove. Those who wore an AC glove and those wearing a CM glove presented average overall finger temperatures significantly lower on the non-dominant hand (products) than the dominant hand (knife) (p < 0.001).

Brain Encoding of Naturalistic, Continuous, and Unpredictable Tactile Events.

Studies employing EEG to measure somatosensory responses have been typically optimized to compute event-related potentials in response to discrete events. However, tactile interactions involve continuous processing of nonstationary inputs that change in location, duration, and intensity. To fill this gap, this study aims to demonstrate the possibility of measuring the neural tracking of continuous and unpredictable tactile information. Twenty-seven young adults (females, 15) were continuously and passively stimulated with a random series of gentle brushes on single fingers of each hand, which were covered from view. Thus, tactile stimulations were unique for each participant and stimulated fingers. An encoding model measured the degree of synchronization between brain activity and continuous tactile input, generating a temporal response function (TRF). Brain topographies associated with the encoding of each finger stimulation showed a contralateral response at central sensors starting at 50 ms and peaking at ∼140 ms of lag, followed by a bilateral response at ∼240 ms. A series of analyses highlighted that reliable tactile TRF emerged after just 3 min of stimulation. Strikingly, topographical patterns of the TRF allowed discriminating digit lateralization across hands and digit representation within each hand. Our results demonstrated for the first time the possibility of using EEG to measure the neural tracking of a naturalistic, continuous, and unpredictable stimulation in the somatosensory domain. Crucially, this approach allows the study of brain activity following individualized, idiosyncratic tactile events to the fingers.

Visual Feature-Guided Diamond Convolutional Network for Finger Vein Recognition.

Finger vein (FV) biometrics have garnered considerable attention due to their inherent non-contact nature and high security, exhibiting tremendous potential in identity authentication and beyond. Nevertheless, challenges pertaining to the scarcity of training data and inconsistent image quality continue to impede the effectiveness of finger vein recognition (FVR) systems. To tackle these challenges, we introduce the visual feature-guided diamond convolutional network (dubbed 'VF-DCN'), a uniquely configured multi-scale and multi-orientation convolutional neural network. The VF-DCN showcases three pivotal innovations: Firstly, it meticulously tunes the convolutional kernels through multi-scale Log-Gabor filters. Secondly, it implements a distinctive diamond-shaped convolutional kernel architecture inspired by human visual perception. This design intelligently allocates more orientational filters to medium scales, which inherently carry richer information. In contrast, at extreme scales, the use of orientational filters is minimized to simulate the natural blurring of objects at extreme focal lengths. Thirdly, the network boasts a deliberate three-layer configuration and fully unsupervised training process, prioritizing simplicity and optimal performance. Extensive experiments are conducted on four FV databases, including MMCBNU_6000, FV_USM, HKPU, and ZSC_FV. The experimental results reveal that VF-DCN achieves remarkable improvement with equal error rates (EERs) of 0.17%, 0.19%, 2.11%, and 0.65%, respectively, and Accuracy Rates (ACC) of 100%, 99.97%, 98.92%, and 99.36%, respectively. These results indicate that, compared with some existing FVR approaches, the proposed VF-DCN not only achieves notable recognition accuracy but also shows fewer number of parameters and lower model complexity. Moreover, VF-DCN exhibits superior robustness across diverse FV databases.

A multi-network model of Parkinson's disease tremor: exploring the finger-dimmer-switch theory and role of dopamine in thalamic self-inhibition.

Background. Tremor is a cardinal symptom of Parkinson's disease (PD) that manifests itself through complex oscillatory activity across multiple neuronal populations. According to the finger-dimmer-switch (FDS) theory, tremor is triggered by transient pathological activity in the basal ganglia-thalamo-cortical (BTC) network (the finger) and transitions into an oscillatory form within the inner circuitry of the thalamus (the switch). The cerebello-thalamo-cortical (CTC) network (the dimmer) is then involved in sustaining and amplifying tremor amplitude. In this study, we aimed to investigate the generation and progression dynamics of PD tremor oscillations by developing a comprehensive and interacting FDS model that transitions sequentially from healthy to PD to tremor and then to tremor-off state.Methods.We constructed a computational model consisting of 700 neurons in 11 regions of BTC, CTC, and thalamic networks. Transition from healthy to PD state was simulated through modulating dopaminergic synaptic connections; and further from PD to tremor and tremor-off by modulating projections between the thalamic reticular nucleus (TRN), anterior ventrolateral nucleus (VLa), and posterior ventrolateral nucleus (VLp).Results.Sustained oscillations in the frequency range of PD tremor emerged in thalamic VLp (5 Hz) and cerebellar dentate nucleus (3 Hz). Increasing self-inhibition in the thalamus through dopaminergic modulation significantly decreased tremor amplitude.Conclusion/Significance.Our results confirm the mechanistic power of the FDS theory in describing the PD tremor phenomenon and emphasize the role of dopaminergic modulation on thalamic self-inhibition. These insights pave the way for novel therapeutic strategies aimed at reducing the tremor by strengthening thalamic self-inhibition, particularly in dopamine-resistant patients.

Inter-Digit Low Level Force Coordination in a Complex Isometric Pinch Tracking Task.

This study examined whether target pursuit tracking by a performer-controlled computer cursor around a square diamond-shaped circuit, using isometric pinch grip force production, would show a significant difference in performance metrics dependent on the clockwise sense of the target movement along the trajectory path. The target template incorporated path segments requiring all four possible combinations of directional force modulation patterns (increasing and decreasing isometric pinch forces of the thumb and index finger). Overall, it was found that cursor positional accuracy was greater during counterclockwise pursuit, that steadiness was greater during clockwise pursuit, and that the cursor bearing angle with respect to target movement was biased toward cursor positioning being within the interior of the trajectory circuit regardless of clockwise sense.

Bioinspired adaptable multiplanar mechano-vibrotactile haptic system.

Several gaps persist in haptic device development due to the multifaceted nature of the sense of touch. Existing gaps include challenges enhancing touch feedback fidelity, providing diverse haptic sensations, and ensuring wearability for delivering tactile stimuli to the fingertips. Here, we introduce the Bioinspired Adaptable Multiplanar Haptic system, offering mechanotactile/steady and vibrotactile pulse stimuli with adjustable intensity (up to 298.1 mN) and frequencies (up to 130 Hz). This system can deliver simultaneous stimuli across multiple fingertip areas. The paper includes a full characterisation of our system. As the device can play an important role in further understanding human touch, we performed human stimuli sensitivity and differentiation experiments to evaluate the capability of delivering mechano-vibrotactile, variable intensity, simultaneous, multiplanar and operator agnostic stimuli. Our system promises to accelerate the development of touch perception devices, providing painless, operator-independent data crucial for researching and diagnosing touch-related disorders.

Artificial embodiment displaces cortical neuromagnetic somatosensory responses.

Integrating artificial limbs as part of one's body involves complex neuroplastic changes resulting from various sensory inputs. While somatosensory feedback is crucial, plastic processes that enable embodiment remain unknown. We investigated this using somatosensory evoked fields (SEFs) in the primary somatosensory cortex (S1) following the Rubber Hand Illusion (RHI), known to quickly induce artificial limb embodiment. During electrical stimulation of the little finger and thumb, 19 adults underwent neuromagnetic recordings before and after the RHI. We found early SEF displacement, including an illusion-brain correlation between extent of embodiment and specific changes to the first cortical response at 20 ms in Area 3b, within S1. Furthermore, we observed a posteriorly directed displacement at 35 ms towards Area 1, known to be important for visual integration during touch perception. That this second displacement was unrelated to extent of embodiment implies a functional distinction between neuroplastic changes of these components and areas. The earlier shift in Area 3b may shape extent of limb ownership, while subsequent displacement into Area 1 may relate to early visual-tactile integration that initiates embodiment. Here we provide evidence for multiple neuroplastic processes in S1-lasting beyond the illusion-supporting integration of artificial limbs like prostheses within the body representation.

I tap myself, and you tap me: bimanual predictive and reactive grip force control as a function of age.

We investigated the effect of age on predictive and reactive grip force control. We compared the coupling between the grip and load force when participants tapped the object (i.e., self-TAP condition) held in their contralateral hand or when the experimenter tapped the object (i.e., external-TAP condition). Participants held the object either with their dominant or their non-dominant hands. Neurophysiological changes occur in the brain throughout childhood, so we hypothesized that these changes would make motor prediction less reliable in adolescents than adults. We compared adolescents' predictive and reactive grip force control (n = 19) to adults (n = 19). We quantified the coupling between grip and load forces using cross-correlation. The lags determined whether peak grip force occurred before (predictive control) or after (reactive control) peak load force. In the self-TAP condition, the change in grip force occurred significantly earlier in adults compared to adolescents by ~ 24 ms for the dominant and ~ 12 ms for the non-dominant hands. During the external-TAP condition, the peak grip force lagged the peak load force for both groups, but the lags were shorter for adolescents than adults for both hands. Smaller finger sizes with larger neural afferent density could enhance the cutaneous reflex responses caused by the sudden change in loading. For the self-TAP condition, results confirmed less efficient motor prediction in adolescents. Morphological and neurophysiological changes unfold in the developing brain during childhood; they can introduce variability into the neural circuits responsible for refining motor prediction.

Zero-Biased Bionic Fingertip E-Skin with Multimodal Tactile Perception and Artificial Intelligence for Augmented Touch Awareness.

Electronic skins (E-Skins) are crucial for future robotics and wearable devices to interact with and perceive the real world. Prior research faces challenges in achieving comprehensive tactile perception and versatile functionality while keeping system simplicity for lack of multimodal sensing capability in a single sensor. Two kinds of tactile sensors, transient voltage artificial neuron (TVAN) and sustained potential artificial neuron (SPAN), featuring self-generated zero-biased signals are developed to realize synergistic sensing of multimodal information (vibration, material, texture, pressure, and temperature) in a single device instead of complex sensor arrays. Simultaneously, machine learning with feature fusion is applied to fully decode their output information and compensate for the inevitable instability of applied force, speed, etc, in real applications. Integrating TVAN and SPAN, the formed E-Skin achieves holistic touch awareness in only a single unit. It can thoroughly perceive an object through a simple touch without strictly controlled testing conditions, realize the capability to discern surface roughness from 0.8 to 1600 µm, hardness from 6HA to 85HD, and correctly distinguish 16 objects with temperature variance from 0 to 80 °C. The E-skin also features a simple and scalable fabrication process, which can be integrated into various devices for broad applications.

Menstrual Cycle Variations in Wearable-Detected Finger Temperature and Heart Rate, But Not in Sleep Metrics, in Young and Midlife Individuals.

Most studies about the menstrual cycle are laboratory-based, in small samples, with infrequent sampling, and limited to young individuals. Here, we use wearable and diary-based data to investigate menstrual phase and age effects on finger temperature, sleep, heart rate (HR), physical activity, physical symptoms, and mood. A total of 116 healthy females, without menstrual disorders, were enrolled: 67 young (18-35 years, reproductive stage) and 53 midlife (42-55 years, late reproductive to menopause transition). Over one menstrual cycle, participants wore Oura ring Gen2 to detect finger temperature, HR, heart rate variability (root mean square of successive differences between normal heartbeats [RMSSD]), steps, and sleep. They used luteinizing hormone (LH) kits and daily rated sleep, mood, and physical symptoms. A cosinor rhythm analysis was applied to detect menstrual oscillations in temperature. The effect of menstrual cycle phase and group on all other variables was assessed using hierarchical linear models. Finger temperature followed an oscillatory trend indicative of ovulatory cycles in 96 participants. In the midlife group, the temperature rhythm's mesor was higher, but period, amplitude, and number of days between menses and acrophase were similar in both groups. In those with oscillatory temperatures, HR was lowest during menses in both groups. In the young group only, RMSSD was lower in the late-luteal phase than during menses. Overall, RMSSD was lower, and number of daily steps was higher, in the midlife group. No significant menstrual cycle changes were detected in wearable-derived or self-reported measures of sleep efficiency, duration, wake-after-sleep onset, sleep onset latency, or sleep quality. Mood positivity was higher around ovulation, and physical symptoms manifested during menses. Temperature and HR changed across the menstrual cycle; however, sleep measures remained stable in these healthy young and midlife individuals. Further work should investigate over longer periods whether individual- or cluster-specific sleep changes exist, and if a buffering mechanism protects sleep from physiological changes across the menstrual cycle.

Human movement strategies in uncertain environments: A synergy-based approach to the stability-agility tradeoff.

Humans frequently prepare for agile movements by decreasing stability. This facilitates transitions between movements but increases vulnerability to external disruptions. Therefore, humans might weigh the risk of disruption against the gain in agility and scale their stability to the likelihood of having to perform an agility-demanding action. We used the theory of motor synergies to investigate how humans manage this stability-agility tradeoff under uncertainty. This theory has long quantified stability using the synergy index, and reduction in stability before movement transitions using anticipatory synergy adjustment (ASA). However, the impact of uncertainty - whether a quick action should be executed or inhibited - on ASA is unknown. Furthermore, the impact of ASA on execution and inhibition of the action is unclear. We combined multi-finger, isometric force production with the go/no-go paradigm. Thirty participants performed constant force (no-go task), rapid force pulse (go task), and randomized go and no-go trials (go/no-go task) in response to visual cues. We measured the pre-cue finger forces and computed ASA using the uncontrolled manifold method and quantified the spatio-temporal features of the force after the visual cue. We expected ASA in both go/no-go and go tasks, but larger ASA for the latter. Surprisingly, we observed ASA only for the go task. For the go/no-go task, 53% of participants increased stability before the cue. The high stability hindered performance, leading to increased errors in no-go trials and lower peak forces in go trials. These results align with the stability-agility tradeoff. It is puzzling why some participants increased stability even though 80% of the trials demanded agility. This study indicates that individual differences in the effect of task uncertainty and motor inhibition on ASA is unexplored in motor synergy theory and presents a method for further development.