Pressure-Insensitive Epidermal Thickness of Fingertip Skin for Optical Image Encryption.

In this study, an internal fingerprint-guided epidermal thickness of fingertip skin is proposed for optical image encryption based on optical coherence tomography (OCT) combined with U-Net architecture of a convolutional neural network (CNN). The epidermal thickness of fingertip skin is calculated by the distance between the upper and lower boundaries of the epidermal layer in cross-sectional optical coherence tomography (OCT) images, which is segmented using CNN, and the internal fingerprint at the epidermis-dermis junction (DEJ) is extracted based on the maximum intensity projection (MIP) algorithm. The experimental results indicate that the internal fingerprint-guided epidermal thickness is insensitive to pressure due to normal correlation coefficients and the encryption process between epidermal thickness maps of fingertip skin under different pressures. In addition, the result of the numerical simulation demonstrates the feasibility and security of the encryption scheme by structural similarity index matrix (SSIM) analysis between the original image and the recovered image with the correct and error keys decryption, respectively. The robustness is analyzed based on the SSIM value in three aspects: different pressures, noise attacks, and data loss. Key randomness is valid by the gray histograms, and the average correlation coefficients of adjacent pixelated values in three directions and the average entropy were calculated. This study suggests that the epidermal thickness of fingertip skin could be seen as important biometric information for information encryption.

Towards humanlike grasp in robotic hands: mechanical implementation of force synergies.

In the field of robotic hands, finger force coordination is usually achieved by complex mechanical structures and control systems. This study presents the design of a novel transmission system inspired from the physiological concept of force synergies, aiming to simplify the control of multifingered robotic hands. To this end, we collected human finger force data during six isometric grasping tasks, and force synergies (i.e. the synergy weightings and the corresponding activation coefficients) were extracted from the concatenated force data to explore their potential for force modulation. We then implemented two force synergies with a cable-driven transmission mechanism consisting of two spring-loaded sliders and five V-shaped bars. Specifically, we used fixed synergy weightings to determine the stiffness of the compression springs, and the displacements of sliders were determined by time-varying activation coefficients. The derived transmission system was then used to drive a five-finger robotic hand named SYN hand. We also designed a motion encoder to selectively activate desired fingers, making it possible for two motors to empower a variety of hand postures. Experiments on the prototype demonstrate successful grasp of a wide range of objects in everyday life, and the finger force distribution of SYN hand can approximate that of human hand during six typical tasks. To our best knowledge, this study shows the first attempt to mechanically implement force synergies for finger force modulation in a robotic hand. In comparison to state-of-the-art robotic hands with similar functionality, the proposed hand can distribute humanlike force ratios on the fingers by simple position control, rather than resorting to additional force sensors or complex control strategies. The outcome of this study may provide alternatives for the design of novel anthropomorphic robotic hands, and thus show application prospects in the field of hand prostheses and exoskeletons.

Monte Carlo simulation of the effect of melanin concentration on light-tissue interactions in transmittance and reflectance finger photoplethysmography.

Photoplethysmography (PPG) uses light to detect volumetric changes in blood, and is integrated into many healthcare devices to monitor various physiological measurements. However, an unresolved limitation of PPG is the effect of skin pigmentation on the signal and its impact on PPG based applications such as pulse oximetry. Hence, an in-silico model of the human finger was developed using the Monte Carlo (MC) technique to simulate light interactions with different melanin concentrations in a human finger, as it is the primary determinant of skin pigmentation. The AC/DC ratio in reflectance PPG mode was evaluated at source-detector separations of 1 mm and 3 mm as the convergence rate (Q), a parameter that quantifies the accuracy of the simulation, exceeded a threshold of 0.001. At a source-detector separation of 3 mm, the AC/DC ratio of light skin was 0.472 times more than moderate skin and 6.39 than dark skin at 660 nm, and 0.114 and 0.141 respectively at 940 nm. These findings are significant for the development of PPG-based sensors given the ongoing concerns regarding the impact of skin pigmentation on healthcare devices.

Metacarpophalangeal joint reconstruction using a costal osteochondral graft: A case report.

RATIONALE: The conventional treatment of giant cell tumors is intralesional curettage with local adjuvant therapy. Because hand tumors have a high local recurrence, the primary goal for treating tumors of the hand is to eradicate the lesion. PATIENT CONCERNS: To preserve the metacarpophalangeal (MCP) joint function as well as avoid further recurrence after surgery. DIAGNOSES: The giant cell tumor invades the patient's MCP joint in an index proximal phalanx. INTERVENTIONS: Using computer-aided design and three-dimensional printing techniques, we reformed the original shapes of the MCP joint and its peripheral bone to replica models. The surgeon then performed an en bloc resection and proximal phalanx with MCP joint reconstruction by fabricating the patient's costal osteochondral graft during the operation. OUTCOMES: After 6 months of rehabilitation, the patient's finger functions could pinch and grasp objects naturally. At the 1-year follow-up, the range of motion of the MCP, proximal interphalangeal, and distal interphalangeal joints improved from flexion of 35° to 60°, 75° to 85°, and 60° to 80°, respectively. The hand function achieved the mean performance of non-preferred hands for young females at the postoperative 3-year follow-up. LESSONS: The customized prototyping technique has the potential to replica the original patient's bony graft to reach the goal of minimizing the defects at the donor site and maximizing the function of the reconstructed MCP joint.

Cortical activations associated with spatial remapping of finger touch using EEG.

The spatial coding of tactile information is functionally essential for touch-based shape perception and motor control. However, the spatiotemporal dynamics of how tactile information is remapped from the somatotopic reference frame in the primary somatosensory cortex to the spatiotopic reference frame remains unclear. This study investigated how hand position in space or posture influences cortical somatosensory processing. Twenty-two healthy subjects received electrical stimulation to the right thumb (D1) or little finger (D5) in three position conditions: palm down on right side of the body (baseline), hand crossing the body midline (effect of position), and palm up (effect of posture). Somatosensory-evoked potentials (SEPs) were recorded using electroencephalography. One early-, two mid-, and two late-latency neurophysiological components were identified for both fingers: P50, P1, N125, P200, and N250. D1 and D5 showed different cortical activation patterns: compared with baseline, the crossing condition showed significant clustering at P1 for D1, and at P50 and N125 for D5; the change in posture showed a significant cluster at N125 for D5. Clusters predominated at centro-parietal electrodes. These results suggest that tactile remapping of fingers after electrical stimulation occurs around 100-125 ms in the parietal cortex.

Deficits in force production during multifinger tasks demarcate cognitive dysfunction.

BACKGROUND: The multifinger force deficit (MFFD) is the decline in force generated by each finger as the number of fingers contributing to an action is increased. It has been shown to associate with cognitive status. AIMS: The aim was to establish whether a particularly challenging form of multifinger grip dynamometry, that provides minimal tactile feedback via cutaneous receptors and requires active compensation for reaction forces, will yield an MFFD that is more sensitive to cognitive status. METHODS: Associations between measures of motor function, and cognitive status (Montreal Cognitive Assessment [MoCA]) and latent components of cognitive function (derived from 11 tests using principal component analysis), were estimated cross-sectionally using generalized partial rank correlations. The participants (n = 62) were community dwelling, aged 65-87. RESULTS: Approximately half the participants were unable to complete the dynamometry task successfully. Cognitive status demarcated individuals who could perform the task from those who could not. Among those who complied with the task requirements, the MFFD was negatively correlated with MoCA scores-those with the highest MoCA scores tended to exhibit the smallest deficits, and vice versa. There were corresponding associations with latent components of cognitive function. DISCUSSION: The results support the view that neurodegenerative processes that are a feature of normal and pathological aging exert corresponding effects on expressions of motor coordination-in multifinger tasks, and cognitive sufficiency, due to their dependence on shared neural systems. CONCLUSIONS: The outcomes add weight to the assertion that deficits in force production during multifinger tasks are sensitive to cognitive dysfunction.

Effects of sensory afferent input on motor cortex excitability of agonist and antagonist muscles.

In this study, we aimed to analyze control mechanisms of short-latency afferent inhibition (SAI) during motor output exertion from an agonist or antagonist muscle. The motor task involved index finger abduction (agonist) and adduction (antagonist). In Experiment 1, motor-evoked potentials (MEPs) were recorded from the first dorsal interosseous (FDI) muscle with and without SAI at three output force levels. In Experiment 2, MEPs were recorded with and without SAI at various time points immediately before the muscle output. Experiment 1 showed that inhibition decreased with an increase in muscle output in the agonist muscle but increased in the antagonist muscle. Experiment 2 showed a decreasing trend of inhibition in the agonist muscle immediately before contraction but showed no significant change in the antagonist muscle. MEPs without electrical stimulation during the reaction time increased in both directions of movement as compared to those in the resting state. These results suggest that SAI modulation strongly influences smooth motor output. Analyzing the inhibitory or enhanced mechanisms during the performance of motor output by SAI in patients with motor impairment and comparing them with the mechanisms seen in healthy participants will improve our understanding of the neurophysiological mechanisms relevant to various situations (e.g., rehabilitation and sports).

Novel near E-Field Topography Sensor for Human-Machine Interfacing in Robotic Applications.

This work investigates a new sensing technology for use in robotic human-machine interface (HMI) applications. The proposed method uses near E-field sensing to measure small changes in the limb surface topography due to muscle actuation over time. The sensors introduced in this work provide a non-contact, low-computational-cost, and low-noise method for sensing muscle activity. By evaluating the key sensor characteristics, such as accuracy, hysteresis, and resolution, the performance of this sensor is validated. Then, to understand the potential performance in intention detection, the unmodified digital output of the sensor is analysed against movements of the hand and fingers. This is done to demonstrate the worst-case scenario and to show that the sensor provides highly targeted and relevant data on muscle activation before any further processing. Finally, a convolutional neural network is used to perform joint angle prediction over nine degrees of freedom, achieving high-level regression performance with an RMSE value of less than six degrees for thumb and wrist movements and 11 degrees for finger movements. This work demonstrates the promising performance of this novel approach to sensing for use in human-machine interfaces.

PHF6-mediated transcriptional control of NSC via Ephrin receptors is impaired in the intellectual disability syndrome BFLS.

The plant homeodomain zinc-finger protein, PHF6, is a transcriptional regulator, and PHF6 germline mutations cause the X-linked intellectual disability (XLID) Börjeson-Forssman-Lehmann syndrome (BFLS). The mechanisms by which PHF6 regulates transcription and how its mutations cause BFLS remain poorly characterized. Here, we show genome-wide binding of PHF6 in the developing cortex in the vicinity of genes involved in central nervous system development and neurogenesis. Characterization of BFLS mice harbouring PHF6 patient mutations reveals an increase in embryonic neural stem cell (eNSC) self-renewal and a reduction of neural progenitors. We identify a panel of Ephrin receptors (EphRs) as direct transcriptional targets of PHF6. Mechanistically, we show that PHF6 regulation of EphR is impaired in BFLS mice and in conditional Phf6 knock-out mice. Knockdown of EphR-A phenocopies the PHF6 loss-of-function defects in altering eNSCs, and its forced expression rescues defects of BFLS mice-derived eNSCs. Our data indicate that PHF6 directly promotes Ephrin receptor expression to control eNSC behaviour in the developing brain, and that this pathway is impaired in BFLS.

MeshID: Few-Shot Finger Gesture Based User Identification Using Orthogonal Signal Interference.

Radio frequency (RF) technology has been applied to enable advanced behavioral sensing in human-computer interaction. Due to its device-free sensing capability and wide availability on Internet of Things devices. Enabling finger gesture-based identification with high accuracy can be challenging due to low RF signal resolution and user heterogeneity. In this paper, we propose MeshID, a novel RF-based user identification scheme that enables identification through finger gestures with high accuracy. MeshID significantly improves the sensing sensitivity on RF signal interference, and hence is able to extract subtle individual biometrics through velocity distribution profiling (VDP) features from less-distinct finger motions such as drawing digits in the air. We design an efficient few-shot model retraining framework based on first component reverse module, achieving high model robustness and performance in a complex environment. We conduct comprehensive real-world experiments and the results show that MeshID achieves a user identification accuracy of 95.17% on average in three indoor environments. The results indicate that MeshID outperforms the state-of-the-art in identification performance with less cost.

Unsupervised neural decoding for concurrent and continuous multi-finger force prediction.

Reliable prediction of multi-finger forces is crucial for neural-machine interfaces. Various neural decoding methods have progressed substantially for accurate motor output predictions. However, most neural decoding methods are performed in a supervised manner, i.e., the finger forces are needed for model training, which may not be suitable in certain contexts, especially in scenarios involving individuals with an arm amputation. To address this issue, we developed an unsupervised neural decoding approach to predict multi-finger forces using spinal motoneuron firing information. We acquired high-density surface electromyogram (sEMG) signals of the finger extensor muscle when subjects performed single-finger and multi-finger tasks of isometric extensions. We first extracted motor units (MUs) from sEMG signals of the single-finger tasks. Because of inevitable finger muscle co-activation, MUs controlling the non-targeted fingers can also be recruited. To ensure an accurate finger force prediction, these MUs need to be teased out. To this end, we clustered the decomposed MUs based on inter-MU distances measured by the dynamic time warping technique, and we then labeled the MUs using the mean firing rate or the firing rate phase amplitude. We merged the clustered MUs related to the same target finger and assigned weights based on the consistency of the MUs being retained. As a result, compared with the supervised neural decoding approach and the conventional sEMG amplitude approach, our new approach can achieve a higher R2 (0.77 ± 0.036 vs. 0.71 ± 0.11 vs. 0.61 ± 0.09) and a lower root mean square error (5.16 ± 0.58 %MVC vs. 5.88 ± 1.34 %MVC vs. 7.56 ± 1.60 %MVC). Our findings can pave the way for the development of accurate and robust neural-machine interfaces, which can significantly enhance the experience during human-robotic hand interactions in diverse contexts.

Prototype and evaluation of automatic fingertip-blood-sampling system that uses fingertip blood-vessel images to determine puncture position.

We are developing an automatic fingertip-blood-sampling system to reduce the burden on trained medical personnel. For this system to withdraw a consistent volume of sampled blood for blood tests, we developed a mechanism for our system to select and puncture the vicinity of a large blood vessel from the blood-vessel image of an individual's fingertip. We call this mechanism the fingertip-vessel-puncture mechanism. From the results of an experiment in which the fingertips of 20 individuals (men and women in their 20 s to 60 s) were manually punctured at near and far locations from the blood vessel selected with our mechanism, the following conclusions were obtained. The fingertip-vessel-puncture mechanism tends to increase the volume of sampled blood, thus is effective in sampling more than 650 µL of blood for automatic blood analyzers. It was also found that it is more effective in increasing the volume of sampled blood in the men and those who were younger.

Effects of finger pinch motor imagery on short-latency afferent inhibition and corticospinal excitability.

Motor imagery is a cognitive process involving the simulation of motor actions without actual movements. Despite the reported positive effects of motor imagery training on motor function, the underlying neurophysiological mechanisms have yet to be fully elucidated. Therefore, the purpose of the present study was to investigate how sustained tonic finger-pinching motor imagery modulates sensorimotor integration and corticospinal excitability using short-latency afferent inhibition (SAI) and single-pulse transcranial magnetic stimulation (TMS) assessments, respectively. Able-bodied individuals participated in the study and assessments were conducted under two experimental conditions in a randomized order between participants: (1) participants performed motor imagery of a pinch task while observing a visual image displayed on a monitor (Motor Imagery), and (2) participants remained at rest with their eyes fixed on the monitor displaying a cross mark (Control). For each condition, sensorimotor integration and corticospinal excitability were evaluated during sustained tonic motor imagery in separate sessions. Sensorimotor integration was assessed by SAI responses, representing inhibition of motor-evoked potentials (MEPs) in the first dorsal interosseous muscle elicited by TMS following median nerve stimulation. Corticospinal excitability was assessed by MEP responses elicited by single-pulse TMS. There was no significant difference in the magnitude of SAI responses between motor imagery and Control conditions, while MEP responses were significantly facilitated during the Motor Imagery condition compared to the Control condition. These findings suggest that motor imagery facilitates corticospinal excitability, without altering sensorimotor integration, possibly due to insufficient activation of the somatosensory circuits or lack of afferent feedback during sustained tonic motor imagery.

Functioning Free Muscle Transplantation to Restore Finger Movement for Sequalae of Volkmann Ischemic Contracture.

Volkmann ischemic contracture (VIC) is a devastating condition that results from neglected compartment syndrome, which leads to prolonged ischemia, irreversible tissue necrosis, and various degrees of muscle and nerve damage, causing serious motor and sensory functional implications for the limb and a spectrum of diseases associated with worsening deformities. A thorough understanding of the anatomy and VIC pathophysiology is needed to plan an appropriate strategy. Functioning free muscle transplantation (FFMT) can restore finger movement in a paralyzed limb but requires a three-staged approach to maximize the benefits of FFMT, leading to meaningful finger extrinsic function.

Finger counting, finger number gesturing, and basic numerical skills: A cross-sectional study in 3- to 5-year-olds.

Recent evidence suggests that using finger-based strategies is beneficial for the acquisition of basic numerical skills. There are basically two finger-based strategies to be distinguished: (a) finger counting (i.e., extending single fingers successively) and (b) finger number gesturing (i.e., extending fingers simultaneously to represent magnitudes). In this study, we investigated both spontaneous and prompted finger counting and finger number gesturing as well as their contribution to basic numerical skills in 3- to 5-year-olds (N = 156). Results revealed that only 6% of children spontaneously used their fingers for counting when asked to name a specific number of animals, whereas 59% applied finger number gesturing to show their age. This indicates that the spontaneous use of finger-based strategies depends heavily on the specific context. Moreover, children performed significantly better in prompted finger counting than in finger number gesturing, suggesting that both strategies build on each other. Finally, both prompted finger counting and finger number gesturing significantly and individually predicted counting, cardinal number knowledge, and basic arithmetic. These results indicate that finger counting and finger number gesturing follow and positively relate to numerical development.

An Atlas of the Human Nail.

Dermatologic literature describes nail abnormalities involving nail bed as linear erythronychia or onychomatricoma. The abnormality reflects cognitive content of the nail bed. A resourceful epidermis capable of manifesting in a variety of clinical appearances depends on initiating stimulus affecting remarkably its nail bed matrix cells. These cells are stem cells (NBMSC) migrating distally to cover remarkably the underlying nail bed dermal ridges that are homologous to finger print dermal ridges. Normally, adult nail bed epidermal cells are uniform and keratinize with the stratum corneum without a granular layer.

Effects of evidence-based nursing care interventions on wound pain and wound complications following surgery for finger tendon injury.

We conducted this study aimed to examine the impact of evidence-based nursing interventions on postoperative wound pain and complications after surgery for finger tendon injury. A total of 86 patients treated for finger tendon injuries at our hospital from January 2021 to October 2023 were selected and randomly divided into an experimental group and a control group. The control group received conventional nursing care, while the experimental group received evidence-based nursing interventions. The study compared the postoperative wound pain intensity, incidence of complications and patient satisfaction with nursing care between the two groups. The analysis revealed that compared with conventional care, evidence-based nursing interventions significantly reduced the level of wound pain (p = 0.034) and the incidence of complications (4.65% vs. 18.60%, p = 0.043). It also increased patient satisfaction with the nursing care (97.67% vs. 83.72%, p = 0.026). The study indicates that the application of evidence-based nursing interventions for patients with finger tendon injuries can reduce postoperative wound pain, decrease the incidence of complications and enhance patient satisfaction with nursing care.