Bayesian Estimation of Potential Performance Improvement Elicited by Robot-Guided Training
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ABSTRACT:
SUBMITTER: Takai A
PROVIDER: S-EPMC8567031 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Motor deficits are linked to a range of negative physical, social and academic consequences. Haptic robotic interventions, based on the principles of sensorimotor learning, have been shown previously to help children with motor problems learn new movements. We therefore examined whether the training benefits of a robotic system would generalise to a standardised test of 'pen-skills', assessed using objective kinematic measures [via the Clinical Kinematic Assessment Tool, CKAT]. A counterbalanced, cross-over design was used in a group of 51 children (37 male, aged 5-11 years) with manual control difficulties. Improved performance on a novel task using the robotic device could be attributed to the intervention but there was no evidence of generalisation to any of the CKAT tasks. The robotic system appears to have the potential to support motor learning, with the technology affording numerous advantages. However, the training regime may need to target particular manual skills (e.g. letter formation) in order to obtain clinically significant improvements in specific skills such as handwriting.
| S-EPMC4788189 | biostudies-literature
Project description:BackgroundIn the past years, robotic systems have become increasingly popular in upper limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm superior efficacy of robotic therapy over conventional methods. The personalization of robot-aided therapy according to the patients' individual motor deficits has been suggested as a pivotal step to improve the clinical outcome of such approaches.MethodsHere, we present a model-based approach to personalize robot-aided rehabilitation therapy within training sessions. The proposed method combines the information from different motor performance measures recorded from the robot to continuously estimate patients' motor improvement for a series of point-to-point reaching movements in different directions. Additionally, it comprises a personalization routine to automatically adapt the rehabilitation training. We engineered our approach using an upper-limb exoskeleton. The implementation was tested with 17 healthy subjects, who underwent a motor-adaptation paradigm, and two subacute stroke patients, exhibiting different degrees of motor impairment, who participated in a pilot test undergoing rehabilitative motor training.ResultsThe results of the exploratory study with healthy subjects showed that the participants divided into fast and slow adapters. The model was able to correctly estimate distinct motor improvement progressions between the two groups of participants while proposing individual training protocols. For the two pilot patients, an analysis of the selected motor performance measures showed that both patients were able to retain the improvements gained during training when reaching movements were reintroduced at a later stage. These results suggest that the automated training adaptation was appropriately timed and specifically tailored to the abilities of each individual.ConclusionsThe results of our exploratory study demonstrated the feasibility of the proposed model-based approach for the personalization of robot-aided rehabilitation therapy. The pilot test with two subacute stroke patients further supported our approach, while providing encouraging results for the applicability in clinical settings. Trial registration This study is registered in ClinicalTrials.gov (NCT02770300, registered 30 March 2016, https://clinicaltrials.gov/ct2/show/NCT02770300).
| S-EPMC7227346 | biostudies-literature
Project description:ObjectiveThere have been no clinical studies comparing different robotic techniques. We compare minimally invasive, robot-guided transforaminal lumbar interbody fusion (RGTLIF) and mini-open robot-guided posterior lumbar interbody fusion (RG-PLIF).MethodsUsing data from a prospective institutional registry, we identified 38 patients who underwent RG-PLIF. Propensity score matching using a nearest-neighbor algorithm was implemented to select RG-TLIF controls. Twelve-month patient-reported outcome measures are presented. A reduction of ≥ 30% from baseline was defined as the minimum clinically important difference (MCID).ResultsAmong the 76 included patients, there was no difference between RG-TLIF and RG-PLIF in surgical time (132.3 ± 29.4 minutes vs. 156.5 ± 53.0 minutes, p = 0.162), length of stay (55.9 ± 20.0 hours vs. 57.2 ± 18.8 hours, p = 0.683), and radiation dose area product (310.6 ± 126.1 mGy × cm2 vs. 287.9 ± 90.3 mGy × cm2, p = 0.370). However, while there was no difference among the 2 groups in terms of raw postoperative patient-reported outcome measures scores (all p > 0.05), MCID in leg pain was greater for RG-PLIF (55.3% vs. 78.9%, p = 0.028), and MCID in Oswestry Disability Index was greater for RG-TLIF (92.1% vs. 68.4%, p = 0.009). There was no difference concerning back pain (81.6% vs. 68.4%, p = 0.185).ConclusionOur findings suggest that both RG-TLIF and RG-PLIF are viable and equally effective techniques in robotic spine surgery.
| S-EPMC8021835 | biostudies-literature
Project description:This study examined the trainability of the proprioceptive sense and explored the relationship between proprioception and motor learning. With vision blocked, human learners had to perform goal-directed wrist movements relying solely on proprioceptive/haptic cues to reach several haptically specified targets. One group received additional somatosensory movement error feedback in form of vibro-tactile cues applied to the skin of the forearm. We used a haptic robotic device for the wrist and implemented a 3-day training regimen that required learners to make spatially precise goal-directed wrist reaching movements without vision. We assessed whether training improved the acuity of the wrist joint position sense. In addition, we checked if sensory learning generalized to the motor domain and improved spatial precision of wrist tracking movements that were not trained. The main findings of the study are: First, proprioceptive acuity of the wrist joint position sense improved after training for the group that received the combined proprioceptive/haptic and vibro-tactile feedback (VTF). Second, training had no impact on the spatial accuracy of the untrained tracking task. However, learners who had received VTF significantly reduced their reliance on haptic guidance feedback when performing the untrained motor task. That is, concurrent VTF was highly salient movement feedback and obviated the need for haptic feedback. Third, VTF can be also provided by the limb not involved in the task. Learners who received VTF to the contralateral limb equally benefitted. In conclusion, somatosensory training can significantly enhance proprioceptive acuity within days when learning is coupled with vibro-tactile sensory cues that provide feedback about movement errors. The observable sensory improvements in proprioception facilitates motor learning and such learning may generalize to the sensorimotor control of the untrained motor tasks. The implications of these findings for neurorehabilitation are discussed.
| S-EPMC5058482 | biostudies-literature
Project description:BackgroundFast changes in human demographics worldwide, coupled with increased mobility, and modified land uses make the threat of emerging infectious diseases increasingly important. Currently there is worldwide alert for H5N1 avian influenza becoming as transmissible in humans as seasonal influenza, and potentially causing a pandemic of unprecedented proportions. Here we show how epidemiological surveillance data for emerging infectious diseases can be interpreted in real time to assess changes in transmissibility with quantified uncertainty, and to perform running time predictions of new cases and guide logistics allocations.Methodology/principal findingsWe develop an extension of standard epidemiological models, appropriate for emerging infectious diseases, that describes the probabilistic progression of case numbers due to the concurrent effects of (incipient) human transmission and multiple introductions from a reservoir. The model is cast in terms of surveillance observables and immediately suggests a simple graphical estimation procedure for the effective reproductive number R (mean number of cases generated by an infectious individual) of standard epidemics. For emerging infectious diseases, which typically show large relative case number fluctuations over time, we develop a bayesian scheme for real time estimation of the probability distribution of the effective reproduction number and show how to use such inferences to formulate significance tests on future epidemiological observations.Conclusions/significanceViolations of these significance tests define statistical anomalies that may signal changes in the epidemiology of emerging diseases and should trigger further field investigation. We apply the methodology to case data from World Health Organization reports to place bounds on the current transmissibility of H5N1 influenza in humans and establish a statistical basis for monitoring its evolution in real time.
| S-EPMC2366072 | biostudies-literature
Project description:The period immediately after the offset of visual training is thought to be critical for memory consolidation. Nevertheless, we still lack direct evidence for the causal role of this period to perceptual learning of either previously or subsequently trained material. To address these issues, we had human subjects complete two consecutive trainings with different tasks (detecting different Gabor orientations). We applied continuous theta burst stimulation (cTBS) to either the visual cortex or a control site (vertex) immediately after the offset of the first training. In the vertex cTBS condition, subjects showed improvement on the first task but not on the second task, suggesting the presence of anterograde interference. Critically, cTBS to the visual cortex abolished the performance improvement on the first task and released the second training from the anterograde interference. These results provide causal evidence for a role of the immediate post-training period in the consolidation of perceptual learning.
| S-EPMC6711956 | biostudies-literature
Project description:BackgroundSystems biology increasingly relies on deep sequencing with combinatorial index tags to associate biological sequences with their sample, cell, or molecule of origin. Accurate data interpretation depends on the ability to classify sequences based on correct decoding of these combinatorial barcodes. The probability of correct decoding is influenced by both sequence quality and the number and arrangement of barcodes. The rising complexity of experimental designs calls for a probability model that accounts for both sequencing errors and random noise, generalizes to multiple combinatorial tags, and can handle any barcoding scheme. The needs for reproducibility and community benchmark standards demand a peer-reviewed tool that preserves decoding quality scores and provides tunable control over classification confidence that balances precision and recall. Moreover, continuous improvements in sequencing throughput require a fast, parallelized and scalable implementation.Results and discussionWe developed a flexible, robustly engineered software that performs probabilistic decoding and supports arbitrarily complex barcoding designs. Pheniqs computes the full posterior decoding error probability of observed barcodes by consulting basecalling quality scores and prior distributions, and reports sequences and confidence scores in Sequence Alignment/Map (SAM) fields. The product of posteriors for multiple independent barcodes provides an overall confidence score for each read. Pheniqs achieves greater accuracy than minimum edit distance or simple maximum likelihood estimation, and it scales linearly with core count to enable the classification of > 11 billion reads in 1 h 15 m using < 50 megabytes of memory. Pheniqs has been in production use for seven years in our genomics core facility.ConclusionWe introduce a computationally efficient software that implements both probabilistic and minimum distance decoders and show that decoding barcodes using posterior probabilities is more accurate than available methods. Pheniqs allows fine-tuning of decoding sensitivity using intuitive confidence thresholds and is extensible with alternative decoders and new error models. Any arbitrary arrangement of barcodes is easily configured, enabling computation of combinatorial confidence scores for any barcoding strategy. An optimized multithreaded implementation assures that Pheniqs is faster and scales better with complex barcode sets than existing tools. Support for POSIX streams and multiple sequencing formats enables easy integration with automated analysis pipelines.
| S-EPMC8254269 | biostudies-literature
Project description:Bayesian estimation is a powerful but underutilized tool for answering drug development questions. In this tutorial, the principles of Bayesian model development, assessment, and prior selection will be outlined. An example pharmacokinetic (PK) model will be used to demonstrate the implementation of Bayesian modeling using the nonlinear mixed-effects modeling software NONMEM.
| S-EPMC10864934 | biostudies-literature
Project description:Background?:Simulation training is an effective method to teach neonatal resuscitation (NR), yet many pediatrics residents do not feel comfortable with NR. Rapid cycle deliberate practice (RCDP) allows the facilitator to provide debriefing throughout the session. In RCDP, participants work through the scenario multiple times, eventually reaching more complex tasks once basic elements have been mastered. Objective?:We determined if pediatrics residents have improved observed abilities, confidence level, and recall in NR after receiving RCDP training compared to the traditional simulation debriefing method. Methods?:Thirty-eight pediatrics interns from a large academic training program were randomized to a teaching simulation session using RCDP or simulation debriefing methods. The primary outcome was the intern's cumulative score on the initial Megacode Assessment Form (MCAF). Secondary outcome measures included surveys of confidence level, recall MCAF scores at 4 months, and time to perform critical interventions. Results?:Thirty-four interns were included in analysis. Interns in the RCDP group had higher initial MCAF scores (89% versus 84%, P?<?.026), initiated positive pressure ventilation within 1 minute (100% versus 71%, P?<?.05), and administered epinephrine earlier (152 s versus 180 s, P?<?.039). Recall MCAF scores were not different between the 2 groups. Conclusions?:Immediately following RCDP interns had improved observed abilities and decreased time to perform critical interventions in NR simulation as compared to those trained with the simulation debriefing. RCDP was not superior in improving confidence level or retention.
| S-EPMC5901799 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2024-03-26 | GSE234010 | GEO