Use of Enzymatically Converted Cell-Free DNA (cfDNA) Data for Copy Number Variation-Linked Fragmentation Analysis Allows for Early Colorectal Cancer Detection.

The use of non-invasive liquid biopsy-based cell-free DNA (cfDNA) analysis is an emerging method of cancer detection and intervention. Different analytical methodologies are used to investigate cfDNA characteristics, resulting in costly and long analysis processes needed for combining different data. This study investigates the possibility of using cfDNA data converted for methylation analysis for combining the cfDNA fragment size with copy number variation (CNV) in the context of early colorectal cancer detection. Specifically, we focused on comparing enzymatically and bisulfite-converted data for evaluating cfDNA fragments belonging to chromosome 18. Chromosome 18 is often reported to be deleted in colorectal cancer. We used counts of short and medium cfDNA fragments of chromosome 18 and trained a linear model (LDA) on a set of 2959 regions to predict early-stage (I-IIA) colorectal cancer on an independent test set. In total, 87.5% sensitivity and 92% specificity were obtained on the enzymatically converted libraries. Repeating the same workflow on bisulfite-converted data yielded lower accuracy results with 58.3% sensitivity, implying that enzymatic conversion preserves the cancer fragmentation footprint in whole genome data better than bisulfite conversion. These results could serve as a promising new avenue for the early detection of colorectal cancer using fragmentation and methylation approaches on the same datasets.

Comparing Recalibration Strategies for Electroencephalography-Based Decoders of Movement Intention in Neurological Patients with Motor Disability.

Motor rehabilitation based on the association of electroencephalographic (EEG) activity and proprioceptive feedback has been demonstrated as a feasible therapy for patients with paralysis. To promote long-lasting motor recovery, these interventions have to be carried out across several weeks or even months. The success of these therapies partly relies on the performance of the system decoding movement intentions, which normally has to be recalibrated to deal with the nonstationarities of the cortical activity. Minimizing the recalibration times is important to reduce the setup preparation and maximize the effective therapy time. To date, a systematic analysis of the effect of recalibration strategies in EEG-driven interfaces for motor rehabilitation has not yet been performed. Data from patients with stroke (4 patients, 8 sessions) and spinal cord injury (SCI) (4 patients, 5 sessions) undergoing two different paradigms (self-paced and cue-guided, respectively) are used to study the performance of the EEG-based classification of motor intentions. Four calibration schemes are compared, considering different combinations of training datasets from previous and/or the validated session. The results show significant differences in classifier performances in terms of the true and false positives (TPs) and (FPs). Combining training data from previous sessions with data from the validation session provides the best compromise between the amount of data needed for calibration and the classifier performance. With this scheme, the average true (false) positive rates obtained are 85.3% (17.3%) and 72.9% (30.3%) for the self-paced and the cue-guided protocols, respectively. These results suggest that the use of optimal recalibration schemes for EEG-based classifiers of motor intentions leads to enhanced performances of these technologies, while not requiring long calibration phases prior to starting the intervention.

Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals.

BACKGROUND: Gait training for individuals with neurological disorders is challenging in providing the suitable assistance and more adaptive behaviour towards user needs. The user specific adaptation can be defined based on the user interaction with the orthosis and by monitoring the user intentions. In this paper, an adaptive control model, commanded by the user intention, is evaluated using a lower limb exoskeleton with incomplete spinal cord injury individuals (SCI). METHODS: A user intention based adaptive control model has been developed and evaluated with 4 incomplete SCI individuals across 3 sessions of training per individual. The adaptive control model modifies the joint impedance properties of the exoskeleton as a function of the human-orthosis interaction torques and the joint trajectory evolution along the gait sequence, in real time. The volitional input of the user is identified by monitoring the neural signals, pertaining to the user's motor activity. These volitional inputs are used as a trigger to initiate the gait movement, allowing the user to control the initialization of the exoskeleton movement, independently. A Finite-state machine based control model is used in this set-up which helps in combining the volitional orders with the gait adaptation. RESULTS: The exoskeleton demonstrated an adaptive assistance depending on the patients' performance without guiding them to follow an imposed trajectory. The exoskeleton initiated the trajectory based on the user intention command received from the brain machine interface, demonstrating it as a reliable trigger. The exoskeleton maintained the equilibrium by providing suitable assistance throughout the experiments. A progressive change in the maximum flexion of the knee joint was observed at the end of each session which shows improvement in the patient performance. Results of the adaptive impedance were evaluated by comparing with the application of a constant impedance value. Participants reported that the movement of the exoskeleton was flexible and the walking patterns were similar to their own distinct patterns. CONCLUSIONS: This study demonstrates that user specific adaptive control can be applied on a wearable robot based on the human-orthosis interaction torques and modifying the joints' impedance properties. The patients perceived no external or impulsive force and felt comfortable with the assistance provided by the exoskeleton. The main goal of such a user dependent control is to assist the patients' needs and adapt to their characteristics, thus maximizing their engagement in the therapy and avoiding slacking. In addition, the initiation directly controlled by the brain allows synchronizing the user's intention with the afferent stimulus provided by the movement of the exoskeleton, which maximizes the potentiality of the system in neuro-rehabilitative therapies.

Application of a model to analyze shoulder biomechanics in adult patients with spinal cord injury when walking with crutches in two different gait patterns.

BACKGROUND: Specific biomechanical models have been developed to study gait using crutches. Clinical application of these models is needed in adult spinal cord injury (SCI) population walking with different patterns of gait with crutches to prevent overuse shoulder injuries. OBJECTIVE: To apply a biomechanical model in a clinical environment to analyze shoulder in adult SCI patients walking with two different patterns of gait with crutches: two point reciprocal gait (RG) and swing-through gait (SG). METHODS: Load cells were fixed to the distal ends and forearm cuffs of a pair of crutches. An active markers system was used for kinematics. Five cycles for each gait pattern were analyzed applying a biomechanical model of the upper limbs. Fifteen subjects with SCI were analyzed. RESULTS: The flexo-extension range of motion was significantly greater when using SG (p < 0.01). Similarly, the superior, posterior and medial forces were significantly stronger for SG in all 3 directions. Flexion, adduction and internal rotation torques were also greater in SG (p < 0.01). CONCLUSIONS: A biomechanical model was successfully applied to study shoulder biomechanics in adult patients with SCI walking with crutches in two different gait patterns. Greater loads exerted on the shoulder walking with SG were confirmed compared to RG.

Control of an Ambulatory Exoskeleton with a Brain-Machine Interface for Spinal Cord Injury Gait Rehabilitation.

The closed-loop control of rehabilitative technologies by neural commands has shown a great potential to improve motor recovery in patients suffering from paralysis. Brain-machine interfaces (BMI) can be used as a natural control method for such technologies. BMI provides a continuous association between the brain activity and peripheral stimulation, with the potential to induce plastic changes in the nervous system. Paraplegic patients, and especially the ones with incomplete injuries, constitute a potential target population to be rehabilitated with brain-controlled robotic systems, as they may improve their gait function after the reinforcement of their spared intact neural pathways. This paper proposes a closed-loop BMI system to control an ambulatory exoskeleton-without any weight or balance support-for gait rehabilitation of incomplete spinal cord injury (SCI) patients. The integrated system was validated with three healthy subjects, and its viability in a clinical scenario was tested with four SCI patients. Using a cue-guided paradigm, the electroencephalographic signals of the subjects were used to decode their gait intention and to trigger the movements of the exoskeleton. We designed a protocol with a special emphasis on safety, as patients with poor balance were required to stand and walk. We continuously monitored their fatigue and exertion level, and conducted usability and user-satisfaction tests after the experiments. The results show that, for the three healthy subjects, 84.44 ± 14.56% of the trials were correctly decoded. Three out of four patients performed at least one successful BMI session, with an average performance of 77.6 1 ± 14.72%. The shared control strategy implemented (i.e., the exoskeleton could only move during specific periods of time) was effective in preventing unexpected movements during periods in which patients were asked to relax. On average, 55.22 ± 16.69% and 40.45 ± 16.98% of the trials (for healthy subjects and patients, respectively) would have suffered from unexpected activations (i.e., false positives) without the proposed control strategy. All the patients showed low exertion and fatigue levels during the performance of the experiments. This paper constitutes a proof-of-concept study to validate the feasibility of a BMI to control an ambulatory exoskeleton by patients with incomplete paraplegia (i.e., patients with good prognosis for gait rehabilitation).

Upper limb rehabilitation after spinal cord injury: a treatment based on a data glove and an immersive virtual reality environment.

UNLABELLED: Purpose state: The aim of this preliminary study was to test a data glove, CyberTouch™, combined with a virtual reality (VR) environment, for using in therapeutic training of reaching movements after spinal cord injury (SCI). METHOD: Nine patients with thoracic SCI were selected to perform a pilot study by comparing two treatments: patients in the intervention group (IG) conducted a VR training based on the use of a data glove, CyberTouch™ for 2 weeks, while patients in the control group (CG) only underwent the traditional rehabilitation. Furthermore, two functional parameters were implemented in order to assess patient's performance of the sessions: normalized trajectory lengths and repeatability. RESULTS: Although no statistical significance was found, the data glove group seemed to obtain clinical changes in the muscle balance (MB) and functional parameters, and in the dexterity, coordination and fine grip tests. Moreover, every patient showed variations in at least one of the functional parameters, either along Y-axis trajectory or Z-axis trajectory. CONCLUSIONS: This study might be a step forward for the investigation of new uses of motion capture systems in neurorehabilitation, making it possible to train activities of daily living (ADLs) in motivational environments while measuring objectively the patient's functional evolution. Implications for Rehabilitation Key findings: A motion capture application based on a data glove is presented, for being used as a virtual reality tool for rehabilitation. This application has provided objective data about patient's functional performance. What the study has added: (1) This study allows to open new areas of research based on the use of different motion capture systems as rehabilitation tools, making it possible to train Activities of Daily Living in motivational environments. (2) Furthermore, this study could be a contribution for the development of clinical protocols to identify which types of patients will benefit most from the VR treatments, which interfaces are more suitable to be used in neurorehabilitation, and what types of virtual exercises will work best.

Quantitative assessment based on kinematic measures of functional impairments during upper extremity movements: A review.

BACKGROUND: Quantitative measures of human movement quality are important for discriminating healthy and pathological conditions and for expressing the outcomes and clinically important changes in subjects' functional state. However the most frequently used instruments for the upper extremity functional assessment are clinical scales, that previously have been standardized and validated, but have a high subjective component depending on the observer who scores the test. But they are not enough to assess motor strategies used during movements, and their use in combination with other more objective measures is necessary. The objective of the present review is to provide an overview on objective metrics found in literature with the aim of quantifying the upper extremity performance during functional tasks, regardless of the equipment or system used for registering kinematic data. METHODS: A search in Medline, Google Scholar and IEEE Xplore databases was performed following a combination of a series of keywords. The full scientific papers that fulfilled the inclusion criteria were included in the review. FINDINGS: A set of kinematic metrics was found in literature in relation to joint displacements, analysis of hand trajectories and velocity profiles. These metrics were classified into different categories according to the movement characteristic that was being measured. INTERPRETATION: These kinematic metrics provide the starting point for a proposed objective metrics for the functional assessment of the upper extremity in people with movement disorders as a consequence of neurological injuries. Potential areas of future and further research are presented in the Discussion section.

Kinematic metrics based on the virtual reality system Toyra as an assessment of the upper limb rehabilitation in people with spinal cord injury.

The aim of this study was to develop new strategies based on virtual reality that can provide additional information to clinicians for the rehabilitation assessment. Virtual reality system Toyra has been used to record kinematic information of 15 patients with cervical spinal cord injury (SCI) while performing evaluation sessions using the mentioned system. Positive correlation, with a moderate and very strong association, has been found between clinical scales and kinematic data, considering only the subscales more closely related to the upper limb function. A set of metrics was defined combining these kinematic data to obtain parameters of reaching amplitude, joint amplitude, agility, accuracy, and repeatability during the evaluation sessions of the virtual reality system Toyra. Strong and moderate correlations have been also found between the metrics reaching and joint amplitude and the clinical scales.