Hand Control Research Articles

Prediction and classification of sEMG-based pinch force between different fingers

The movement of intelligent EMG-driven prosthesis mainly relies on the synergy of different fingers to achieve function of grasping objects. The paper proposes a novel scheme for force prediction and movement classification about pinch between different fingers based on surface electromyography (sEMG) using machine learning. The pinch force and sEMG signals are recorded synchronously by a data acquisition device. Eight features are extracted, which are proven to have better performance in the estimation of sEMG-to-force. We present a novel feature selection method that uses the one-dimensional time series similarity assessment based on Manhattan distance to eliminate the repetitive information between features. Three optimal features carrying less repetitive information are retained. Seven machine learning algorithms are used to predict force strength. The results show that the Long Short Term Memory (LSTM) has the best performance of force prediction, achieving a R2 of 0.9517 and RMSE of 3.2723. The paper proposes a novel method of converting EMG feature sequences to the normalized gray image in order to classify the finger movement. Five classifiers based on image feature extraction and the Convolutional Neural Network (CNN) are developed respectively. The experimental results indicate that the CNN performs best, achieving an accuracy of 97.66%. In this way, it not only realizes the accurate force prediction, but also realizes the movement classification between different fingers. The proposed methodology has the potential to realize simultaneous force and movement control of prosthetic hand.

New Highly Portable Simulator (SECMA) Based on Virtual Reality for Teaching Essential Skills in Minimally Invasive Surgeries

This study presents a new minimal access surgery training system, SECMA, and its constructive validation to determine its usefulness for training basic laparoscopic skills. SECMA is an affordable, highly portable, mobile virtual reality training tool for laparoscopic techniques that integrates the Oculus Quest with a mechanical interface for surgeon simulation of forceps using the hand controllers of these devices. It allows the execution of structured activities (supported by virtual scenarios simulating operating rooms developed in Unity), performance evaluation, and real-time data capture. Two experiments were carried out: 1) coordination; and 2) capture and transport, with a total of 21 individuals divided into two groups: a novice group (inexperienced) of 10 participants and an expert group (>100 endoscopic procedures) of 11 participants. Total task time score, right-hand speed, path length, and other metrics from several consecutive runs on the simulator were compared between experts and novices. Data automatically recorded by SECMA during the experiments were analyzed using hypothesis tests, linear regressions, analysis of variance, principal component analysis, and machine learning-supervised classifiers. In the experiments, the experts scored significantly better than the novices in all the parameters used. The tasks evaluated discriminated between the skills of experienced and novice surgeons, giving the first indication of construct validity for SECMA.

Highly Stable Ladder‐Type Conjugated Polymer Based Organic Electrochemical Transistors for Low Power and Signal Processing‐Free Surface Electromyogram Triggered Robotic Hand Control

AbstractOrganic electrochemical transistors (OECTs) based complementary inverters have been considered as promising candidates in electrophysiological amplification, owing to their low power consumption, and high gain. To create complementary inverters, it is important to use highly stable p‐type and n‐type polymers with well‐balanced current. In this study, the electrochemical stability of p‐type ladder‐conjugated polymer‐based OECT is improved through an annealing process that maintains its doped‐state drain current from 76% to 105% after 4,500 cycles in ambient environment. Next an OECT‐based complementary inverter made from p‐type and n‐type ladder‐conjugated polymers (PBBTL and BBL) that possess ultra‐low power consumption (≈170 nW), high gain (67 V/V), and high noise margin (92%) with full rail‐to‐rail swing, is presented. Furthermore, its potential for amplifying the envelope of surface electromyography (EMG) for robotic hand control is demonstrated. The high variation in the output (0.35 V) allows the amplified EMG signals to be directly captured by a commercial analog‐to‐digital converter, which in turn controls the robot hand to grasp different objects with low delay and low noise. These results demonstrate the capability of OECT inverter‐based amplifier in future signal processing‐free human‐machine interface, particularly useful for prosthetic control and gesture control applications.

The rubber hand illusion evaluated using different stimulation modalities.

Tactile feedback plays a vital role in inducing ownership and improving motor control of prosthetic hands. However, commercially available prosthetic hands typically do not provide tactile feedback and because of that the prosthetic user must rely on visual input to adjust the grip. The classical rubber hand illusion (RHI) where a brush is stroking the rubber hand, and the user's hidden hand synchronously can induce ownership of a rubber hand. In the classic RHI the stimulation is modality-matched, meaning that the stimulus on the real hand matches the stimulus on the rubber hand. The RHI has also been used in previous studies with a prosthetic hand as the "rubber hand," suggesting that a hand prosthesis can be incorporated within the amputee's body scheme. Interestingly, previous studies have shown that stimulation with a mismatched modality, where the rubber hand was brushed, and vibrations were felt on the hidden hand also induced the RHI. The aim of this study was to compare how well mechanotactile, vibrotactile, and electrotactile feedback induced the RHI in able-bodied participants and forearm amputees. 27 participants with intact hands and three transradial amputees took part in a modified RHI experiment. The rubber hand was stroked with a brush, and the participant's hidden hand/residual limb received stimulation with either brush stroking, electricity, pressure, or vibration. The three latter stimulations were modality mismatched with regard to the brushstroke. Participants were tested for ten different combinations (stimulation blocks) where the stimulations were applied on the volar (glabrous skin), and dorsal (hairy skin) sides of the hand. Outcome was assessed using two standard tests (questionnaire and proprioceptive drift). All types of stimulation induced RHI but electrical and vibration stimulation induced a stronger RHI than pressure. After completing more stimulation blocks, the proprioceptive drift test showed that the difference between pre- and post-test was reduced. This indicates that the illusion was drifting toward the rubber hand further into the session.

Developing a virtual reality (VR) application for practicing the ABCDE approach for systematic clinical observation

BackgroundThe Airways, Breathing, Circulation, Disability, Exposure (ABCDE) approach is an international approach for systematic clinical observation. It is an essential clinical skill for medical and healthcare professionals and should be practiced repeatedly. One way to do so is by using virtual reality (VR). The aim was therefore to develop a VR application to be used by inexperienced health students and professionals for self-instructed practice of systematic clinical observation using the ABCDE approach.MethodsAn iterative human-centred approach done in three overlapping phases; deciding on the ABCDE approach, specifying the requirements, and developing the application.ResultsA total of 138 persons were involved. Eight clinical observations were included in the ABCDE approach. The requirements included making it possible for inexperienced users to do self-instructed practice, a high level of immersion, and a sense of presence including mirroring the physical activities needed to do the ABCDE approach, allowing for both single and multiplayer, and automatic feedback with encouragement to repeat the training. In addition to many refinements, the testing led to the development of some new solutions. Prominent among them was to get players to understand how to use the VR hand controllers and start to interact with the VR environment and more instructions like showing videos on how to do observations. The solutions in the developed version were categorised into 15 core features like onboarding, instructions, quiz, and feedback.ConclusionA virtual reality application for self-instructed practice of systematic clinical observation using the ABCDE approach can be developed with sufficient testing by inexperienced health students and professionals.

Design and Evaluation of Using Head-Mounted Virtual Reality for Learning Clinical Procedures: Mixed Methods Study.

The capacity of health care professionals to perform clinical procedures safely and competently is crucial as it will directly impact patients' outcomes. Given the ability of head-mounted virtual reality to simulate the authentic clinical environment, this platform should be suitable for nurses to refine their clinical skills for knowledge and skills acquisition. However, research on head-mounted virtual reality in learning clinical procedures is limited. The objectives of this study were (1) to describe the design of a head-mounted virtual reality system and evaluate it for education on clinical procedures for nursing students and (2) to explore the experience of nursing students using head-mounted virtual reality for learning clinical procedures and the usability of the system. This usability study used a mixed method approach. The stages included developing 3D models of the necessary instruments and materials used in intravenous therapy and subcutaneous injection procedures performed by nurses, followed by developing the procedures using the Unreal Engine (Epic Games). Questionnaires on the perception of continuance intention and the System Usability Scale were used along with open-ended questions. Twenty-nine nursing students took part in this questionnaire study after experiencing the immersive virtual reality (IVR) intervention. Participants reported largely favorable game perception and learning experience. Mean perception scores ranged from 3.21 to 4.38 of a maximum score of 5, while the mean system usability score was 53.53 of 100. The majority found that the IVR experience was engaging, and they were immersed in the game. The challenges encountered included unfamiliarity with the new learning format; technological constraints, such as using hand controllers; and physical discomfort. The conception of IVR for learning clinical procedures through deliberate practice to enhance nurses' knowledge and skills is promising. However, refinement of the prototypes is required to improve user experience and learning. Future research can explore other ways to use IVR for better education and health care purposes.

Raw EMG classification using extreme value machine

Electromyogram (EMG) signal is considered as an easy-to-capture (i.e. skin-mounted) and promissing biometric for the control of prosthetic hands. Despite the plethora number of researches on EMG-based control of prosthetics, two major challenges have not sufficiently been addressed , i.e. realtime classification, and robustness against noise. Our contribution in this paper is two fold. First, we have proposed a deep neural network (DNN) model with customized architecture to learn features directly from raw EMG data. In this model, a self-improvement module enhances the accuracy and robustness against artifact. Second, we utilize extreme value machine (EVM) for classification of the learnt feature. EVM models the statistical distribution of the latent space and classifies finger movements based on the maximum cumulative distribution probability to the fitted model. Our experimental results, using public domain EMG data, are very promising. They indicate the average accuracy of 98.5% for 750 msec window for 10-class classification. This result is superior or competitive compared with other online classifications reported in the literature on the same dataset. Additionally, our results illustrate that self-improvement feature learner (SIFL) is much more resistant against the noise than the models that employ engineered features. For example, in presence of severe white noise, the accuracy of our methodology degrades 10−15% compared to 30−50% of others.

Home practice for robotic surgery: a randomized controlled trial of a low-cost simulation model

Pre-operative simulated practice allows trainees to learn robotic surgery outside the operating room without risking patient safety. While simulation practice has shown efficacy, simulators are expensive and frequently inaccessible. Cruff (J Surg Educ 78(2): 379–381, 2021) described a low-cost simulation model to learn hand movements for robotic surgery. Our study evaluates whether practice with low-cost home simulation models can improve trainee performance on robotic surgery simulators. Home simulation kits were adapted from those described by Cruff (J Surg Educ 78(2): 379–381, 2021). Hand controllers were modified to mimic the master tool manipulators (MTMs) on the da Vinci Skills Simulator (dVSS). Medical students completed two da Vinci exercises: Sea Spikes 1 (SS1) and Big Dipper Needle Driving (BDND). They were subsequently assigned to either receive a home simulation kit or not. Students returned two weeks later and repeated SS1 and BDND. Overall score, economy of motion, time to completion, and penalty subtotal were collected, and analyses of covariance were performed. Semi-structured interviews assessed student perceptions of the robotic simulation experience. Thirty-three medical students entered the study. Twenty-nine completed both sessions. The difference in score improvement between the experimental and control groups was not significant. In interviews, students provided suggestions to increase fidelity and usefulness of low-cost robotic home simulation. Low-cost home simulation models did not improve student performance on dVSS after two weeks of at-home practice. Interview data highlighted areas to focus future simulation efforts. Ongoing work is necessary to develop low-cost solutions to facilitate practice for robotic surgery and foster more inclusive and accessible surgical education.

Isolation and Identification of Acinetobacter Spp. from Various Clinical Specimen and their Antibiotic Susceptibility Pattern in PDU Medical College, Rajkot, Gujarat, Western India

Introduction: Up to 25% of healthy adults exhibit cutaneous colonization by Acinetobacter and are the most common Gram-negative bacteria carried on the skin of hospital personnel. They are opportunistic pathogens causes a number of outbreaks of infections but their predominant role is in intensive care units. Such infections are often difficult to treat because of widespread resistance to the major groups of antibiotics. Materials and Methods: Various samples were collected aseptically and transported immediately to the bacteriology laboratory. The pathogens were identified by standard laboratory procedures including Gram’s staining, motility, culture, colony characters and biochemical reactions. Antimicrobial susceptibility testing was performed by modified Kirby Bauer method as per the CLSI guidelines. Result: 128 (3.11%) Acinetobacter spp. were isolated from 4112 specimens. Out of these, 72 from general wards and 46 from ICU and 10 from opd. Males (59.37%) are predominant than females (40.62%). The isolates sensitivite to Meropenem (83.59%) followed by Pipracillin-tazobactum (66.41%), Tetracycline (58.59%). Maximum resistance was observed to Cefotaxime (93.75%) followed by Ceftazidime (92.19%) & Cefepime (89.06%). Conclusions: Acinetobacter are the “superbugs” of the modern hospital environment causing significant infections in specific patient populations, especially in patients of ICU which are prone to cause infections due to over use of broad spectrum antibiotics. Awareness to maintain good housekeeping, equipment decontamination, strict attention to hand washing, isolation procedures and control of antibiotic usage, especially in high-risk areas, appear most likely measures to control the spread of Acinetobacter spp. in hospitals.

Characterization of Atypical Corticospinal Tract Microstructure and Hand Impairments in Early-Onset Hemiplegic Cerebral Palsy: Preliminary Findings.

Unilateral brain injuries occurring before at or shortly after full-term can result in hemiplegic cerebral palsy (HCP). HCP affects one side of the body and can be characterized in the hand with measures of weakness and a loss of independent hand control resulting in mirror movements. Hand impairment severity is extremely heterogeneous across individuals with HCP and the neural basis for this variability is unclear. We used diffusion MRI and tractography to investigate the relationship between structural morphology of the supraspinal corticospinal tract (CST) and the severity of two typical hand impairments experienced by individuals with HCP, grasp weakness and mirror movements. Results from nine children with HCP and eight children with typical development show that there is a significant hemispheric association between CST microstructure and hand impairment severity that may be explained by atypical development and fiber distribution of motor pathways. Further analysis in the non-lesioned (dominant) hemisphere shows significant differences for CST termination in the cortex between participants with HCP and those with typical development. These findings suggest that structural disparities at the cellular level in the seemingly unaffected hemisphere after early unilateral brain injury may be the cause of heterogeneous hand impairments seen in this population.Clinical Relevance- Quantitative measurement of the variability in hand function in individuals with HCP is necessary to represent the distinct impairments experienced by each person. Further understanding of the structural neural morphology underlying distal upper extremity motor deficits after early unilateral brain injury will help lead to the development of more specific targeted interventions that increase functional outcomes.

Toward a novel soft robotic system for minimally invasive interventions.

During minimally invasive surgery, surgeons maneuver tools through complex anatomies, which is difficult without the ability to control the position of the tools inside the body. A potential solution for a substantial portion of these procedures is the efficient design and control of a pneumatically actuated soft robot system. We designed and evaluated a system to control a steerable catheter tip. A macroscale 3D printed catheter tip was designed to have two separately pressurized channels to induce bending in two directions. A motorized hand controller was developed to allow users to control the bending angle while manually inserting the steerable tip. Preliminary characterization of two catheter tip prototypes was performed and used to map desired angle inputs into pressure commands. The integrated robotic system allowed both a novice and a skilled surgeon to position the steerable catheter tip at the location of cylindrical targets with sub-millimeter accuracy. The novice was able to reach each target within ten seconds and the skilled surgeon within five seconds on average. This soft robotic system enables its user to simultaneously insert and bend the pneumatically actuated catheter tip with high accuracy and in a short amount of time. These results show promise concerning the development of a soft robotic system that can improve outcomes in minimally invasive interventions.

Brain Computer Interface Based on Motor Imagery for Mechanical Arm Grasp Control

This paper puts forward a brain computer interface (BCI) system to realize the hand and wrist control using the ABB Mechanical Arm. This BCI system gathers four kinds of motor imaginary (MI) tasks (hand grasp, hand spread, wrist flexion and wrist extension) electroencephalogram (EEG) signals from 30 electrodes. It utilizes two fifth-order Butterworth Band-Pass Filter (BPF) with different bandwidths and normalization method to achieve the raw MI tasks EEG signals preprocessing. The main challenge of feature extraction is to extract enough representative features from MI tasks to classify them. This proposed BCI system extracts eleven kinds of features in time domain and time-frequency domain and uses mutual information method to reduce the large dimension of the extracted features. In addition, the BCI system applies a single convolutional layer Convolutional neural networks (CNN) with 30 filters to implement the quaternary classification of MI tasks. Compared with early researches, the classification accuracy of this BCI system is increased by about 35%. The actual mechanical arm grasping control experiments verifies that this BCI system has good adaptability.

Does surgeon sex and anthropometry matter for tool usability in traditional laparoscopic surgery? A systematic review and meta-analysis.

Hand size, strength, and stature all impact a surgeon's ability to perform Traditional Laparoscopic Surgery (TLS) comfortably and effectively. This is due to limitations in instrument and operating room design. This article aims to review performance, pain, and tool usability data based on biological sex and anthropometry. PubMed, Embase, and Cochrane databases were searched in May 2023. Retrieved articles were screened based on whether a full-text, English article was available in which original results were stratified by biological sex or physical proportions. Article quality was discussed using the Mixed Methods Appraisal Tool (MMAT). Data were summarized in three main themes: task performance, physical discomfort, and tool usability and fit. Task completion times, pain prevalence, and grip style results between male and female surgeons formed three meta-analyses. A total of 1354 articles were sourced, and 54 were deemed suitable for inclusion. The collated results showed that female participants, predominantly novices, took 2.6-30.1s longer to perform standardized laparoscopic tasks. Female surgeons reported pain at double the frequency of their male colleagues. Female surgeons and those with a smaller glove size were consistently more likely to report difficulty and require modified (potentially suboptimal) grip techniques with standard laparoscopic tools. The pain and stress reported by female or small-handed surgeons when using laparoscopic tools demonstrates the need for currently available instrument handles, including robotic hand controls, to become more size-inclusive. However, this study is limited by reporting bias and inconsistencies; furthermore, most data was collected in a simulated environment. Additional research into how anthropometric tool design impacts the live operating performance of experienced female surgeons would further inform this area of investigation.

Fitted avatars: automatic skeleton adjustment for self-avatars in virtual reality

In the era of the metaverse, self-avatars are gaining popularity, as they can enhance presence and provide embodiment when a user is immersed in Virtual Reality. They are also very important in collaborative Virtual Reality to improve communication through gestures. Whether we are using a complex motion capture solution or a few trackers with inverse kinematics (IK), it is essential to have a good match in size between the avatar and the user, as otherwise mismatches in self-avatar posture could be noticeable for the user. To achieve such a correct match in dimensions, a manual process is often required, with the need for a second person to take measurements of body limbs and introduce them into the system. This process can be time-consuming, and prone to errors. In this paper, we propose an automatic measuring method that simply requires the user to do a small set of exercises while wearing a Head-Mounted Display (HMD), two hand controllers, and three trackers. Our work provides an affordable and quick method to automatically extract user measurements and adjust the virtual humanoid skeleton to the exact dimensions. Our results show that our method can reduce the misalignment produced by the IK system when compared to other solutions that simply apply a uniform scaling to an avatar based on the height of the HMD, and make assumptions about the locations of joints with respect to the trackers.

Motorcycle rider arm muscle patterns characterize coordination of hand controls in emergency braking

Motorcycle rider arm muscle patterns characterize coordination of hand controls in emergency braking

Bone structure and composition in a hyperglycemic, obese, and leptin receptor-deficient rat: Microscale characterization of femur and calvarium.

Metabolic abnormalities, such as diabetes mellitus and obesity, can impact bone quantity and/or bone quality. In this work, we characterize bone material properties, in terms of structure and composition, in a novel rat model with congenic leptin receptor (LepR) deficiency, severe obesity, and hyperglycemia (type 2 diabetes-like condition). Femurs and calvaria (parietal region) from 20-week-old male rats are examined to probe bones formed both by endochondral and intramembranous ossification. Compared to the healthy controls, the LepR-deficient animals display significant alterations in femur microarchitecture and in calvarium morphology when analyzed by micro-computed X-ray tomography (micro-CT). In particular, shorter femurs with reduced bone volume, combined with thinner parietal bones and shorter sagittal suture, point towards a delay in the skeletal development of the LepR-deficient rodents. On the other hand, LepR-deficient animals and healthy controls display analogous bone matrix composition, which is assessed in terms of tissue mineral density by micro-CT, degree of mineralization by quantitative backscattered electron imaging, and various metrics extrapolated from Raman hyperspectral images. Some specific microstructural features, i.e., mineralized cartilage islands in the femurs and hyper-mineralized areas in the parietal bones, also show comparable distribution and characteristics in both groups. Overall, the altered bone microarchitecture in the LepR-deficient animals indicates compromised bone quality, despite the normal bone matrix composition. The delayed development is also consistent with observations in humans with congenic Lep/LepR deficiency, making this animal model a suitable candidate for translational research.

Zero Moment Two Edge Pushing of Novel Objects With Center of Mass Estimation

Pushing is one of the fundamental nonprehensile manipulation skills to impart to an object changes in position and orientation. To exploit this skill to manipulate novel objects, explicit knowledge of their physical properties should be given a priori. In this work, we estimate the center of mass (CoM) of an object by narrowing down its probable location with a deep learning model and Mason’s voting theorem. In addition, we propose the Zero Moment Two Edge Pushing (ZMTEP) method to translate a novel object without rotation to a goal pose. The proposed method enables a pusher to select the most suitable two-edge-contact configuration for a given object using the estimated CoM and the geometrical shape of the object. Notably, neither the friction between the object and its support plane nor the friction between the object and the pusher are assumed to be known. We evaluate the proposed CoM estimation and ZMTEP methods through a series of experiments in both simulation and real robotic pusher settings. The result shows that the CoM estimation method has good mean squared error properties and small standard deviation, and the ZMTEP method significantly outperforms competitive baseline methods. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article aims to endow robotic arms with the capability of moving or aligning objects by pushing, which is much more simple and secure than pick-and-place or in-hand manipulations. Most in-demand manipulation skills require sophisticated hand design and control, which might not be affordable for industrial applications staying cost-competitive. In contrast, robot pushing can be implemented with different types of simple pushers and straightforwardly applied to pre-grasp manipulation. This article makes the estimation of an object’s CoM location practical. Building upon the estimation method, a robust and noise-tolerant two-edge-contact pushing configuration selection method is presented to translate an arbitrarily shaped unknown object to its goal pose.

The real-time dynamic online feeder service with a maximum headway at mandatory stops

On the one hand, fully flexible demand-responsive feeder services efficiently tailor their service to passengers' needs. Traditional services, on the other hand, offer predictability and easier cost control. This paper considers a semi-flexible feeder service that combines positive characteristics of both traditional and fully flexible services. There are two types of bus stops in this service. Mandatory bus stops have a maximum allowable headway for bus departures. Optional stops are only visited when there is demand for transportation nearby. When new passenger requests arrive, the performance of this feeder service is optimised in real time. A metaheuristic with two phases is developed to optimise the service. The dynamic optimisation method is compared to a model that optimises the service when all requests are known beforehand. The results show that the dynamic method has an average gap of 6.5% with respect to the static model and an average acceptance rate of 95.1%. A case study in the city of Antwerp shows that, when compared to existing transit options in the region, this feeder service can increase the service quality by 31.6% when enough resources are available.

Autoencoder-based myoelectric controller for prosthetic hands.

In the past, linear dimensionality-reduction techniques, such as Principal Component Analysis, have been used to simplify the myoelectric control of high-dimensional prosthetic hands. Nonetheless, their nonlinear counterparts, such as Autoencoders, have been shown to be more effective at compressing and reconstructing complex hand kinematics data. As a result, they have a potential of being a more accurate tool for prosthetic hand control. Here, we present a novel Autoencoder-based controller, in which the user is able to control a high-dimensional (17D) virtual hand via a low-dimensional (2D) space. We assess the efficacy of the controller via a validation experiment with four unimpaired participants. All the participants were able to significantly decrease the time it took for them to match a target gesture with a virtual hand to an average of and three out of four participants significantly improved path efficiency. Our results suggest that the Autoencoder-based controller has the potential to be used to manipulate high-dimensional hand systems via a myoelectric interface with a higher accuracy than PCA; however, more exploration needs to be done on the most effective ways of learning such a controller.

Efecto de los pesticidas sobre el rendimiento cognitivo y motor en habitantes de zonas rurales del Tolima

Organophosphate pesticides can cause cognitive impairment. However, the farmer uses different pesticides in all phases of the same crop. The aim of this study was to analyze the effect of serial pesticides on cognitive and motor performance in samples of exposed, indirectly exposed, and unexposed people. In the exploratory study with a cross-sectional design, a total of 135 small farmers from the informal sector participated. Mini-Mental, Trail Making, Rey-Osterrieth Complex Figure, Digit Retention, Hopkins Verbal Learning and the Grooved Pegboard tests were administered. The results show that the highest serial exposure occurs with Glyphosate, Lorsban, Furadan and Paraquat. The group with direct exposure to pesticides presented a lower performance in working memory, explicit verbal memory, constructive praxis and fine motor control of the right hand, than the indirectly exposed group and the unexposed group. In conclusion, direct and serial exposure to pesticides generates neuropsychological and motor impairment in informal sector farmers, it is recommended the development of public politics that promote healthy and safe practices, to minimize the risks due to the use of these substances