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ARTICLE ONLINE FIRST This provisional PDF corresponds to the article as it appeared upon acceptan... more ARTICLE ONLINE FIRST This provisional PDF corresponds to the article as it appeared upon acceptance. A copyedited and fully formatted version will be made available soon. The final version may contain major or minor changes. Subscription: Information about subscribing to Minerva Medica journals is online at: http://www.minervamedica.it/en/how-to-order-journals.php Reprints and permissions: For information about reprints and permissions send an email to: journals.dept@minervamedica.it-journals2.dept@minervamedica.it-journals6.dept@minervamedica.it

Papers by Natalie Mrachacz-Kersting

IEEE Transactions on Neural Systems and Rehabilitation Engineering

A proportion of users cannot achieve adequate brain-computer interface (BCI) control. The diversi... more A proportion of users cannot achieve adequate brain-computer interface (BCI) control. The diversity of BCI modalities provides a way to solve this emerging issue. Here, we investigate the accuracy of a somatosensory BCI based on sensory imagery (SI). During the SI tasks, subjects were instructed to imagine a tactile sensation and to maintain the attention on the corresponding hand, as if there was tactile stimulus on the skin of the wrist. The performance across 106 healthy subjects in left-and righthand SI discrimination was 78.9±13.2%. In 70.7% of the subjects the performance was above 70%. The SI task induced a contralateral cortical activation, and high-density EEG

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Objective: We propose a tactile-inducedoscillation approach to reduce the calibration time in som... more Objective: We propose a tactile-inducedoscillation approach to reduce the calibration time in somatosensory brain-computer interfaces (BCI). Methods: Based on the similarity between tactile induced eventrelated desynchronization (ERD) and imagined sensation induced ERD activation, we extensively evaluated BCI performance when using a conventional and a novel calibration strategy. In the conventional calibration, the tactile imagined data was used, while in the sensory calibration model sensory stimulation data was used. Subjects were required to sense the tactile stimulus when real tactile was applied to the left or right wrist and were required to perform imagined sensation tasks in the somatosensory BCI paradigm. Results: The sensory calibration led to a significantly better performance than the conventional

Journal of Neural Engineering, 2021

Objective. A brain–computer interface (BCI) allows users to control external devices using brain ... more Objective. A brain–computer interface (BCI) allows users to control external devices using brain signals that can be recorded non-invasively via electroencephalography (EEG). Movement related cortical potentials (MRCPs) are an attractive option for BCI control since they arise naturally during movement execution and imagination, and therefore, do not require an extensive training. This study tested the feasibility of online detection of reaching and grasping using MRCPs for the application in patients suffering from amyotrophic lateral sclerosis (ALS). Approach. A BCI system was developed to trigger closing of a soft assistive glove by detecting a reaching movement. The custom-made software application included data collection, a novel method for collecting the input data for classifier training from the offline recordings based on a sliding window approach, and online control of the glove. Eight healthy subjects and two ALS patients were recruited to test the developed BCI system. They performed assessment blocks without the glove active (NG), in which the movement detection was indicated by a sound feedback, and blocks (G) in which the glove was controlled by the BCI system. The true positive rate (TPR) and the positive predictive value (PPV) were adopted as the outcome measures. Correlation analysis between forehead EEG detecting ocular artifacts and sensorimotor area EEG was conducted to confirm the validity of the results. Main results. The overall median TPR and PPV were >0.75 for online BCI control, in both healthy individuals and patients, with no significant difference across the blocks (NG versus G). Significance. The results demonstrate that cortical activity during reaching can be detected and used to control an external system with a limited amount of training data (30 trials). The developed BCI system can be used to provide grasping assistance to ALS patients.

2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), 2017

This work proposes a Common Spatial Pattern with Polarity Check (CSPPC) to facilitate Movement Re... more This work proposes a Common Spatial Pattern with Polarity Check (CSPPC) to facilitate Movement Related Cortical Potential (MRCP) detection. The algorithm was compared with the Locality Preserving Projection (LPP) algorithm in the context of detecting foot dorsiflexion within a group of thirteen subjects. It has been shown that CSPPC achieved a significantly reduced delay latency compared to LPP (−25.9±190.7 ms vs. 204.6±123.7 ms), which had a similar detection accuracy (true positive rate: 73.6±23.3% vs. 72.2±16.3%). This proposed algorithm will enhance the induction of neuroplasticity by significantly reducing the delay between movement detection and the corresponding afferent input.

ABSTRACT This paper describes a novel brain-computer interface (BCI) with the aim of motor rehabi... more ABSTRACT This paper describes a novel brain-computer interface (BCI) with the aim of motor rehabilitation of stroke patients. Movement imagination of dorsiflexion was detected from scalp electroencephalogram (EEG) through movement related cortical potentials (MRCP). Such detection subsequently triggered an motorized ankle foot orthosis (MAFO), which induced passive dorsiflexions. The hypothesis was that the cortical drive to the muscle is enhanced over the use of this system because of the afferent flow resulting from the passive movement that mimicked the sensory feedback of movement execution. In the pilot experiment, extracted MRCP parameters changed consistently after the BCI-intervention. Follow-up experiments are underway to further investigate the feasibility of such a BCI-based stroke rehabilitation system and to quantify the accompanying plastic changes.

Converging Clinical and Engineering Research on Neurorehabilitation III, 2018

2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), 2017

Dual tasking refers to the simultaneous execution of two tasks with different demands. In this st... more Dual tasking refers to the simultaneous execution of two tasks with different demands. In this study, we aimed to investigate the effect of a second task on a main task of motor execution and on the ability to detect the cortical potential related to the main task from non-invasive electroencephalographic (EEG). Participants were asked to perform a series of cue-based ankle dorsiflexions as the primary task (single task level). In some experimental runs, in addition to the primary task they concurrently attended an auditory oddball paradigm consisting of three tones while they were asked to count the number of sequences of special tones (dual task level). EEG signals were recorded from nine channels centered on Cz. Analysis of event-related potential (ERP) signals from Cz confirmed that the oddball task decreased the attention to the ankle dorsiflexion significantly. Furthermore, movement-related cortical potential (MRCP) analysis revealed that the amplitude of the MRCP and pre-movement slopes were changed significantly. These variations were significantly greater for the EEG channels corresponding to the motor cortex and the frontal-central cortex.

We have recently developed an associative Brain-Computer Interface (BCI) for neuromodulation in c... more We have recently developed an associative Brain-Computer Interface (BCI) for neuromodulation in chronic and acute stroke patients that leads to functional improvements. The control signal is the movement related cortical potential (MRCP) that develops prior to movement execution. The MRCP increases in variability as a novel task is learned, which in turn significantly decreases the detection accuracy. In the current study we sought to investigate if tactile stimulation, often implemented in rehabilitation, may act as a primer to our associative BCI by decreasing MRCP variability. Six chronic stroke patients were exposed to one session of tactile stimulation, and the MRCP of an arm lifting task, repeated 30 times, extracted. Results reveal that for three patients the MRCP detection accuracy expressed as the rate of true and false positives was improved. In two patients however the detection accuracy declined while one patient was unable to complete the experiment. Since tactile stimu...

Converging Clinical and Engineering Research on Neurorehabilitation III, 2018

Musculoskeletal pain is the most frequent health complaint reported by workers in Europe. Neurofe... more Musculoskeletal pain is the most frequent health complaint reported by workers in Europe. Neurofeedback has been proposed to be an alternative to the current treatment of pain, however, the extent to which musculoskeletal pain alters the electroencephalographic (EEG) signal is still not known. The current study aims at identifying the signal characteristics provoked by musculoskeletal pain during movement. Healthy volunteers and patients diagnosed with Lateral Epicondylalgia performed wrist extension movements while EEG signals were collected. The power of the EEG signal was calculated and differences between healthy volunteers and patients were assessed. EEG activity of pain patients differed significantly from that observed in heathy volunteers within the alpha and beta band. This alteration is movement related and is particularly visible in frontal channel locations. The results of the current study are currently being implemented for the development of a neurofeedback protocol t...

In previous studies we have introduced a brain-computer interface (BCI) system based on movement ... more In previous studies we have introduced a brain-computer interface (BCI) system based on movement related cortical potentials (MRCP). The performance of this system was shown to be significantly affected by the users’ attention state. In the current study, we analyzed MRCP features (low frequencies) and features extracted at higher frequencies to determine the effect of variations in user’s attention on EEG. Attention was modulated by a combination of auditory and visual stimuli that served as external distractors from the main task, which was a simple dorsiflexion. Time and frequency analysis was performed on EEG signals recorded from twenty-eight channels. The amplitude of the peak negativity and the slope of the negative deflection of the MRCP decreased and pre-movement variability increased with the distractors. Moreover, spectral analysis revealed an increment of theta power and alpha power due to attentional shifts. These results have implications for the design of real-life BC...

Osteoarthritis (OA), the number one cause of disability, exceeds 1% of the gross national product... more Osteoarthritis (OA), the number one cause of disability, exceeds 1% of the gross national product in both the UK and US and is increasing in prevalence as the population ages and becomes more obese. Excessive stress damages tissues within the joint, irrespective of the specific biomechanical etiology, and is considered a risk factor for OA. Hence, it is important to monitor joint stress. However, stress cannot be measured in vivo. In vitro experiments are expensive and may not accurately represent in vivo tissue properties. Finite element modelling is a useful computational method to predict joint stress before and after surgical interventions. This is a powerful tool to investigate the impact of surgical procedures on joint stress. The effect of factors, such as tissue geometry, material properties, type of activity and loading conditions, which could affect joint stress, may be investigated in the model. When modelling human tissues, assumptions are made, for example on tissue material properties, which are subject specific and challenging to measure non-destructively. Sensitivity analyses are conducted to identify and simulate, with higher accuracy, those material properties that drive changes in stress magnitude. In this tutorial, participants will use FEBio finite element software, learn how to create simple finite element models and analyse joint stress. Participants will also have the opportunity to work with a first metatarsophalangeal joint finite element model to investigate the effects of different tissue material properties, foot types, and surgical interventions on joint stress.  Dr. Howard Hillstrom (Hospital for Special Surgery) will introduce the application of finite element modelling and the clinical rationale for its use, based upon his 90 studies in lower extremity biomechanics, including the assessment of foot type and musculoskeletal pathology, employing experimental and computational approaches. This introduction will include contemporary examples of biomechanical problems that could be addressed, using finite element models.  Dr. Rajshree Hillstrom (Anglia Ruskin University) will present a step-by-step method for developing a simple finite element model of a joint, using FEBio software. This will include creating and meshing simple geometry representing joint tissues, assigning tissue material properties, boundary conditions to simulate tissue interactions, loading conditions and to predict joint stress. During this hands-on session, participants will develop their own finite element models and run analyses. Dr R Hillstrom will then explain how to develop anatomically complex models. Participants will split in groups and solve for stress in the 1st metatarsophalangeal joint for different tissue properties and surgical corrections.  Oliver Morgan (Anglia Ruskin University) will assist participants with troubleshooting any problems during the hands-on aspect of this tutorial. He will make sure that FEBio is running smoothly on either windows or mac laptops and that participants have all the supporting files to participate in the tutorial.

In this work, the variation of the waveform of the movement related cortical potential (MRCP) was... more In this work, the variation of the waveform of the movement related cortical potential (MRCP) was investigated in a real-time neurofeedback study, in which the spontaneous slow cortical potential (SCP) within the same frequency band as MRCP ([0.05 3] Hz) was provided as feedback to the subjects. Experiments have shown that the background SCP activity has a strong influence on the waveform of the self-paced MRCP. Negative potential SCP has been shown to increase the negative peak of the MRCP waveform, while positive potential SCP has been shown to reduce the negative peak. The variation of the single-trial MRCP waveform was correlated with the background SCP activity. This study provided a new approach to evaluate and modulate MRCP waveform, which directly determines the brain switch detection BCI performance.

ARTICLE ONLINE FIRST This provisional PDF corresponds to the article as it appeared upon acceptan... more ARTICLE ONLINE FIRST This provisional PDF corresponds to the article as it appeared upon acceptance. A copyedited and fully formatted version will be made available soon. The final version may contain major or minor changes. Subscription: Information about subscribing to Minerva Medica journals is online at: http://www.minervamedica.it/en/how-to-order-journals.php Reprints and permissions: For information about reprints and permissions send an email to: journals.dept@minervamedica.it-journals2.dept@minervamedica.it-journals6.dept@minervamedica.it

IEEE Transactions on Neural Systems and Rehabilitation Engineering

A proportion of users cannot achieve adequate brain-computer interface (BCI) control. The diversi... more A proportion of users cannot achieve adequate brain-computer interface (BCI) control. The diversity of BCI modalities provides a way to solve this emerging issue. Here, we investigate the accuracy of a somatosensory BCI based on sensory imagery (SI). During the SI tasks, subjects were instructed to imagine a tactile sensation and to maintain the attention on the corresponding hand, as if there was tactile stimulus on the skin of the wrist. The performance across 106 healthy subjects in left-and righthand SI discrimination was 78.9±13.2%. In 70.7% of the subjects the performance was above 70%. The SI task induced a contralateral cortical activation, and high-density EEG

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Objective: We propose a tactile-inducedoscillation approach to reduce the calibration time in som... more Objective: We propose a tactile-inducedoscillation approach to reduce the calibration time in somatosensory brain-computer interfaces (BCI). Methods: Based on the similarity between tactile induced eventrelated desynchronization (ERD) and imagined sensation induced ERD activation, we extensively evaluated BCI performance when using a conventional and a novel calibration strategy. In the conventional calibration, the tactile imagined data was used, while in the sensory calibration model sensory stimulation data was used. Subjects were required to sense the tactile stimulus when real tactile was applied to the left or right wrist and were required to perform imagined sensation tasks in the somatosensory BCI paradigm. Results: The sensory calibration led to a significantly better performance than the conventional

Journal of Neural Engineering, 2021

Objective. A brain–computer interface (BCI) allows users to control external devices using brain ... more Objective. A brain–computer interface (BCI) allows users to control external devices using brain signals that can be recorded non-invasively via electroencephalography (EEG). Movement related cortical potentials (MRCPs) are an attractive option for BCI control since they arise naturally during movement execution and imagination, and therefore, do not require an extensive training. This study tested the feasibility of online detection of reaching and grasping using MRCPs for the application in patients suffering from amyotrophic lateral sclerosis (ALS). Approach. A BCI system was developed to trigger closing of a soft assistive glove by detecting a reaching movement. The custom-made software application included data collection, a novel method for collecting the input data for classifier training from the offline recordings based on a sliding window approach, and online control of the glove. Eight healthy subjects and two ALS patients were recruited to test the developed BCI system. They performed assessment blocks without the glove active (NG), in which the movement detection was indicated by a sound feedback, and blocks (G) in which the glove was controlled by the BCI system. The true positive rate (TPR) and the positive predictive value (PPV) were adopted as the outcome measures. Correlation analysis between forehead EEG detecting ocular artifacts and sensorimotor area EEG was conducted to confirm the validity of the results. Main results. The overall median TPR and PPV were >0.75 for online BCI control, in both healthy individuals and patients, with no significant difference across the blocks (NG versus G). Significance. The results demonstrate that cortical activity during reaching can be detected and used to control an external system with a limited amount of training data (30 trials). The developed BCI system can be used to provide grasping assistance to ALS patients.

2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), 2017

This work proposes a Common Spatial Pattern with Polarity Check (CSPPC) to facilitate Movement Re... more This work proposes a Common Spatial Pattern with Polarity Check (CSPPC) to facilitate Movement Related Cortical Potential (MRCP) detection. The algorithm was compared with the Locality Preserving Projection (LPP) algorithm in the context of detecting foot dorsiflexion within a group of thirteen subjects. It has been shown that CSPPC achieved a significantly reduced delay latency compared to LPP (−25.9±190.7 ms vs. 204.6±123.7 ms), which had a similar detection accuracy (true positive rate: 73.6±23.3% vs. 72.2±16.3%). This proposed algorithm will enhance the induction of neuroplasticity by significantly reducing the delay between movement detection and the corresponding afferent input.

ABSTRACT This paper describes a novel brain-computer interface (BCI) with the aim of motor rehabi... more ABSTRACT This paper describes a novel brain-computer interface (BCI) with the aim of motor rehabilitation of stroke patients. Movement imagination of dorsiflexion was detected from scalp electroencephalogram (EEG) through movement related cortical potentials (MRCP). Such detection subsequently triggered an motorized ankle foot orthosis (MAFO), which induced passive dorsiflexions. The hypothesis was that the cortical drive to the muscle is enhanced over the use of this system because of the afferent flow resulting from the passive movement that mimicked the sensory feedback of movement execution. In the pilot experiment, extracted MRCP parameters changed consistently after the BCI-intervention. Follow-up experiments are underway to further investigate the feasibility of such a BCI-based stroke rehabilitation system and to quantify the accompanying plastic changes.

Converging Clinical and Engineering Research on Neurorehabilitation III, 2018

2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), 2017

Dual tasking refers to the simultaneous execution of two tasks with different demands. In this st... more Dual tasking refers to the simultaneous execution of two tasks with different demands. In this study, we aimed to investigate the effect of a second task on a main task of motor execution and on the ability to detect the cortical potential related to the main task from non-invasive electroencephalographic (EEG). Participants were asked to perform a series of cue-based ankle dorsiflexions as the primary task (single task level). In some experimental runs, in addition to the primary task they concurrently attended an auditory oddball paradigm consisting of three tones while they were asked to count the number of sequences of special tones (dual task level). EEG signals were recorded from nine channels centered on Cz. Analysis of event-related potential (ERP) signals from Cz confirmed that the oddball task decreased the attention to the ankle dorsiflexion significantly. Furthermore, movement-related cortical potential (MRCP) analysis revealed that the amplitude of the MRCP and pre-movement slopes were changed significantly. These variations were significantly greater for the EEG channels corresponding to the motor cortex and the frontal-central cortex.

We have recently developed an associative Brain-Computer Interface (BCI) for neuromodulation in c... more We have recently developed an associative Brain-Computer Interface (BCI) for neuromodulation in chronic and acute stroke patients that leads to functional improvements. The control signal is the movement related cortical potential (MRCP) that develops prior to movement execution. The MRCP increases in variability as a novel task is learned, which in turn significantly decreases the detection accuracy. In the current study we sought to investigate if tactile stimulation, often implemented in rehabilitation, may act as a primer to our associative BCI by decreasing MRCP variability. Six chronic stroke patients were exposed to one session of tactile stimulation, and the MRCP of an arm lifting task, repeated 30 times, extracted. Results reveal that for three patients the MRCP detection accuracy expressed as the rate of true and false positives was improved. In two patients however the detection accuracy declined while one patient was unable to complete the experiment. Since tactile stimu...

Converging Clinical and Engineering Research on Neurorehabilitation III, 2018

Musculoskeletal pain is the most frequent health complaint reported by workers in Europe. Neurofe... more Musculoskeletal pain is the most frequent health complaint reported by workers in Europe. Neurofeedback has been proposed to be an alternative to the current treatment of pain, however, the extent to which musculoskeletal pain alters the electroencephalographic (EEG) signal is still not known. The current study aims at identifying the signal characteristics provoked by musculoskeletal pain during movement. Healthy volunteers and patients diagnosed with Lateral Epicondylalgia performed wrist extension movements while EEG signals were collected. The power of the EEG signal was calculated and differences between healthy volunteers and patients were assessed. EEG activity of pain patients differed significantly from that observed in heathy volunteers within the alpha and beta band. This alteration is movement related and is particularly visible in frontal channel locations. The results of the current study are currently being implemented for the development of a neurofeedback protocol t...

In previous studies we have introduced a brain-computer interface (BCI) system based on movement ... more In previous studies we have introduced a brain-computer interface (BCI) system based on movement related cortical potentials (MRCP). The performance of this system was shown to be significantly affected by the users’ attention state. In the current study, we analyzed MRCP features (low frequencies) and features extracted at higher frequencies to determine the effect of variations in user’s attention on EEG. Attention was modulated by a combination of auditory and visual stimuli that served as external distractors from the main task, which was a simple dorsiflexion. Time and frequency analysis was performed on EEG signals recorded from twenty-eight channels. The amplitude of the peak negativity and the slope of the negative deflection of the MRCP decreased and pre-movement variability increased with the distractors. Moreover, spectral analysis revealed an increment of theta power and alpha power due to attentional shifts. These results have implications for the design of real-life BC...

Osteoarthritis (OA), the number one cause of disability, exceeds 1% of the gross national product... more Osteoarthritis (OA), the number one cause of disability, exceeds 1% of the gross national product in both the UK and US and is increasing in prevalence as the population ages and becomes more obese. Excessive stress damages tissues within the joint, irrespective of the specific biomechanical etiology, and is considered a risk factor for OA. Hence, it is important to monitor joint stress. However, stress cannot be measured in vivo. In vitro experiments are expensive and may not accurately represent in vivo tissue properties. Finite element modelling is a useful computational method to predict joint stress before and after surgical interventions. This is a powerful tool to investigate the impact of surgical procedures on joint stress. The effect of factors, such as tissue geometry, material properties, type of activity and loading conditions, which could affect joint stress, may be investigated in the model. When modelling human tissues, assumptions are made, for example on tissue material properties, which are subject specific and challenging to measure non-destructively. Sensitivity analyses are conducted to identify and simulate, with higher accuracy, those material properties that drive changes in stress magnitude. In this tutorial, participants will use FEBio finite element software, learn how to create simple finite element models and analyse joint stress. Participants will also have the opportunity to work with a first metatarsophalangeal joint finite element model to investigate the effects of different tissue material properties, foot types, and surgical interventions on joint stress.  Dr. Howard Hillstrom (Hospital for Special Surgery) will introduce the application of finite element modelling and the clinical rationale for its use, based upon his 90 studies in lower extremity biomechanics, including the assessment of foot type and musculoskeletal pathology, employing experimental and computational approaches. This introduction will include contemporary examples of biomechanical problems that could be addressed, using finite element models.  Dr. Rajshree Hillstrom (Anglia Ruskin University) will present a step-by-step method for developing a simple finite element model of a joint, using FEBio software. This will include creating and meshing simple geometry representing joint tissues, assigning tissue material properties, boundary conditions to simulate tissue interactions, loading conditions and to predict joint stress. During this hands-on session, participants will develop their own finite element models and run analyses. Dr R Hillstrom will then explain how to develop anatomically complex models. Participants will split in groups and solve for stress in the 1st metatarsophalangeal joint for different tissue properties and surgical corrections.  Oliver Morgan (Anglia Ruskin University) will assist participants with troubleshooting any problems during the hands-on aspect of this tutorial. He will make sure that FEBio is running smoothly on either windows or mac laptops and that participants have all the supporting files to participate in the tutorial.

In this work, the variation of the waveform of the movement related cortical potential (MRCP) was... more In this work, the variation of the waveform of the movement related cortical potential (MRCP) was investigated in a real-time neurofeedback study, in which the spontaneous slow cortical potential (SCP) within the same frequency band as MRCP ([0.05 3] Hz) was provided as feedback to the subjects. Experiments have shown that the background SCP activity has a strong influence on the waveform of the self-paced MRCP. Negative potential SCP has been shown to increase the negative peak of the MRCP waveform, while positive potential SCP has been shown to reduce the negative peak. The variation of the single-trial MRCP waveform was correlated with the background SCP activity. This study provided a new approach to evaluate and modulate MRCP waveform, which directly determines the brain switch detection BCI performance.