Cultural and translation challenges in assessing health literacy among immigrants from the former Soviet Union.

Health literacy is an important foundation for health promotion and an under-recognized risk factor for immigrant and refugee groups. Yet measuring health literacy among diverse ethnic and linguistic populations presents complex challenges. We describe cultural and translation challenges encountered in measuring health literacy among Russian-speaking immigrants to the USA and offer a mixed-methods approach to understanding them. The Rx-Health Literacy (RxHL) study used cross-sectional quantitative and qualitative data to examine health literacy and medication adherence among five cultural and four language groups (Latinx, Vietnamese, African-American, Russian-speaking immigrant and White American) who are patients at Caring Health Center, a federally qualified health center in Springfield, MA. We translated an existing health literacy scale into Russian and Vietnamese and examined item difficulty across cultural groups. We conducted qualitative cognitive interviews to learn more about Russian speakers' understandings of the scale. Health literacy scores varied by cultural group, and the range of correct responses was much greater among Russian speakers than in other groups. Percentage correct varied by 69.7% for Russian speakers, compared with 25.0-44.0% for other groups. These findings indicate greater variability in health literacy levels among this group compared with others. Cognitive interviews with Russian-speaking participants revealed multiple interpretations of several items, suggesting that the English version of the scale contained embedded meanings associated with an American health care context that were not captured in the translated instrument. Combining qualitative and quantitative research methods allows for greater insight into contextual and translation factors that may shape the results of translated instruments in unanticipated ways.

Suppression of cortical electrostimulation artifacts using pre-whitening and null projection.

Objective.Invasive brain-computer interfaces (BCIs) have shown promise in restoring motor function to those paralyzed by neurological injuries. These systems also have the ability to restore sensation via cortical electrostimulation. Cortical stimulation produces strong artifacts that can obscure neural signals or saturate recording amplifiers. While front-end hardware techniques can alleviate this problem, residual artifacts generally persist and must be suppressed by back-end methods.Approach.We have developed a technique based on pre-whitening and null projection (PWNP) and tested its ability to suppress stimulation artifacts in electroencephalogram (EEG), electrocorticogram (ECoG) and microelectrode array (MEA) signals from five human subjects.Main results.In EEG signals contaminated by narrow-band stimulation artifacts, the PWNP method achieved average artifact suppression between 32 and 34 dB, as measured by an increase in signal-to-interference ratio. In ECoG and MEA signals contaminated by broadband stimulation artifacts, our method suppressed artifacts by 78%-80% and 85%, respectively, as measured by a reduction in interference index. When compared to independent component analysis, which is considered the state-of-the-art technique for artifact suppression, our method achieved superior results, while being significantly easier to implement.Significance.PWNP can potentially act as an efficient method of artifact suppression to enable simultaneous stimulation and recording in bi-directional BCIs to biomimetically restore motor function.

Exercise repetition rate measured with simple sensors at home can be used to estimate Upper Extremity Fugl-Meyer score after stroke.

Introduction: It would be valuable if home-based rehabilitation training technologies could automatically assess arm impairment after stroke. Here, we tested whether a simple measure-the repetition rate (or "rep rate") when performing specific exercises as measured with simple sensors-can be used to estimate Upper Extremity Fugl-Meyer (UEFM) score. Methods: 41 individuals with arm impairment after stroke performed 12 sensor-guided exercises under therapist supervision using a commercial sensor system comprised of two pucks that use force and motion sensing to measure the start and end of each exercise repetition. 14 of these participants then used the system at home for three weeks. Results: Using linear regression, UEFM score was well estimated using the rep rate of one forward-reaching exercise from the set of 12 exercises (r2 = 0.75); this exercise required participants to alternately tap pucks spaced about 20 cm apart (one proximal, one distal) on a table in front of them. UEFM score was even better predicted using an exponential model and forward-reaching rep rate (Leave One Out Cross Validation (LOOCV) r2 = 0.83). We also tested the ability of a nonlinear, multivariate model (a regression tree) to predict UEFM, but such a model did not improve prediction (LOOCV r2 = 0.72). However, the optimal decision tree also used the forward-reaching task along with a pinch grip task to subdivide more and less impaired patients in a way consistent with clinical intuition. At home, rep rate for the forward-reaching exercise well predicted UEFM score using an exponential model (LOOCV r2 = 0.69), but only after we re-estimated coefficients using the home data. Discussion: These results show how a simple measure-exercise rep rate measured with simple sensors-can be used to infer an arm impairment score and suggest that prediction models should be tuned separately for the clinic and home environments.

Content Analysis of Patient-Facing Information Related to Preeclampsia.

BACKGROUND: Previous research has shown pregnant people are not knowledgeable about preeclampsia, a significant cause of maternal morbidity and mortality. This lack of knowledge may impact their ability to report symptoms, comply with recommendations, and receive appropriate follow-up care. Pregnant people commonly seek information from sources outside their treating clinician, including pregnancy-specific books and online sources. We examined commonly used preeclampsia information sources to evaluate whether pregnant people are receiving up-to-date, guideline-based information. METHODS: We conducted a content analysis of preeclampsia-related information in top-ranking websites and bestselling pregnancy books. We used American College of Obstetricians and Gynecologists preeclampsia guidelines to construct a codebook, which we used to examine source content completeness and accuracy. For each source, we analyzed information about preeclampsia diagnosis, patient-reported symptoms, risk factors, prevention, treatment, and complications. RESULTS: Across 19 included sources (13 websites and 6 books), we found substantial variation in completeness and accuracy of preeclampsia information. We found high rates of mentions for preeclampsia symptoms. Risk factors were more commonly included in online sources than book sources. Most sources mentioned treatment options, including blood pressure medication and giving birth; however, one-third of online sources positively mentioned the nonrecommended treatment of bed rest. Prevention methods, including prenatal aspirin for high-risk pregnancies, and long-term complications of preeclampsia were infrequently mentioned. CONCLUSIONS: Varying rates of accuracy in patient-facing preeclampsia information mean there is substantial room for improvement in these sources. Ensuring pregnant people receive current guideline-based information is critical for improving outcomes and implementing shared decision-making.

Artifact propagation in subdural cortical electrostimulation: Characterization and modeling.

Cortical stimulation via electrocorticography (ECoG) may be an effective method for inducing artificial sensation in bi-directional brain-computer interfaces (BD-BCIs). However, strong electrical artifacts caused by electrostimulation may significantly degrade or obscure neural information. A detailed understanding of stimulation artifact propagation through relevant tissues may improve existing artifact suppression techniques or inspire the development of novel artifact mitigation strategies. Our work thus seeks to comprehensively characterize and model the propagation of artifacts in subdural ECoG stimulation. To this end, we collected and analyzed data from eloquent cortex mapping procedures of four subjects with epilepsy who were implanted with subdural ECoG electrodes. From this data, we observed that artifacts exhibited phase-locking and ratcheting characteristics in the time domain across all subjects. In the frequency domain, stimulation caused broadband power increases, as well as power bursts at the fundamental stimulation frequency and its super-harmonics. The spatial distribution of artifacts followed the potential distribution of an electric dipole with a median goodness-of-fit of R 2 = 0.80 across all subjects and stimulation channels. Artifacts as large as ±1,100 µV appeared anywhere from 4.43 to 38.34 mm from the stimulation channel. These temporal, spectral and spatial characteristics can be utilized to improve existing artifact suppression techniques, inspire new strategies for artifact mitigation, and aid in the development of novel cortical stimulation protocols. Taken together, these findings deepen our understanding of cortical electrostimulation and provide critical design specifications for future BD-BCI systems.

A Qualitative Investigation of the Experiences of Tobacco Use among U.S. Adults with Food Insecurity.

BACKGROUND: Low-income U.S. adults experiencing food insecurity have a disproportionately high prevalence of cigarette smoking, and quantitative studies suggest that food insecurity is a barrier to quitting. To guide effective tobacco control strategies, this study aimed to understand the experiences, perceptions, and context of tobacco use and cessation among low-income populations experiencing food insecurity. METHODS: We conducted in-depth, semi-structured interviews with 23 adults who were currently smoking cigarettes and were experiencing food insecurity, mostly living in rural settings. Participants were recruited through food-pantry-based needs assessment surveys and study flyers in community-based organizations. The interview guide explored participants' histories of smoking, the role and function of tobacco in their lives, their interest in and barriers to quitting, as well as lived experiences of food insecurity. We used reflexive thematic analysis to analyze transcribed interviews. RESULTS: Within a broader context of structural challenges related to poverty and financial strain that shaped current smoking behavior and experiences with food insecurity, we identified the following five themes: smoking to ignore hunger or eat less; staying addicted to smoking in the midst of instability; smoking being prioritized in the midst of financial strain; life stressors and the difficulty of quitting smoking and staying quit; and childhood adversity at the intersection of food insecurity and tobacco use. CONCLUSION: The context of tobacco use among adults with food insecurity was highly complex. To effectively address tobacco-related disparities among those who are socially and economically disadvantaged, tobacco control efforts should consider relevant lived experiences and structural constraints intersecting smoking and food insecurity. Findings are applied to a conceptualization of clustering of conditions contributing to nicotine dependence, food insecurity, and stress.

Benchtop and bedside validation of a low-cost programmable cortical stimulator in a testbed for bi-directional brain-computer-interface research.

Introduction: Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback. Methods: A custom programmable direct cortical stimulator (DCS) capable of eliciting artificial sensorimotor response was integrated into an embedded BCI system to form a safe, independent, wireless, and battery powered testbed to explore BD-BCI concepts at a low cost. The BD-BCI stimulator output was tested in phantom brain tissue by assessing its ability to deliver electrical stimulation equivalent to an FDA-approved commercial electrical cortical stimulator. Subsequently, the stimulator was tested in an epilepsy patient with subcortical electrocorticographic (ECoG) implants covering the sensorimotor cortex to assess its ability to elicit equivalent responses as the FDA-approved counterpart. Additional safety features (impedance monitoring, artifact mitigation, and passive and active charge balancing mechanisms) were also implemeneted and tested in phantom brain tissue. Finally, concurrent operation with interleaved stimulation and BCI decoding was tested in a phantom brain as a proof-of-concept operation of BD-BCI system. Results: The benchtop prototype BD-BCI stimulator's basic output features (current amplitude, pulse frequency, pulse width, train duration) were validated by demonstrating the output-equivalency to an FDA-approved commercial cortical electrical stimulator (R 2 > 0.99). Charge-neutral stimulation was demonstrated with pulse-width modulation-based correction algorithm preventing steady state voltage deviation. Artifact mitigation achieved a 64.5% peak voltage reduction. Highly accurate impedance monitoring was achieved with R 2 > 0.99 between measured and actual impedance, which in-turn enabled accurate charge density monitoring. An online BCI decoding accuracy of 93.2% between instructional cues and decoded states was achieved while delivering interleaved stimulation. The brain stimulation mapping via ECoG grids in an epilepsy patient showed that the two stimulators elicit equivalent responses. Significance: This study demonstrates clinical validation of a fully-programmable electrical stimulator, integrated into an embedded BCI system. This low-cost BD-BCI system is safe and readily applicable as a testbed for BD-BCI research. In particular, it provides an all-inclusive hardware platform that approximates the limitations in a near-future implantable BD-BCI. This successful benchtop/human validation of the programmable electrical stimulator in a BD-BCI system is a critical milestone toward fully-implantable BD-BCI systems.

Pre-whitening and Null Projection as an Artifact Suppression Method for Electrocorticography Stimulation in Bi-Directional Brain Computer Interfaces.

Electrocorticography (ECoG)-based bi-directional (BD) brain-computer interfaces (BCIs) are a forthcoming technology promising to help restore function to those with motor and sensory deficits. A major problem with this paradigm is that the cortical stimulation necessary to elicit artificial sensation creates strong electrical artifacts that can disrupt BCI operation by saturating recording amplifiers or obscuring useful neural signal. Even with state-of-the-art hardware artifact suppression methods, robust signal processing techniques are still required to suppress residual artifacts that are present at the digital back-end. Herein we demonstrate the effectiveness of a pre-whitening and null projection artifact suppression method using ECoG data recorded during a clinical neurostimulation procedure. Our method achieved a maximum artifact suppression of 21.49 dB and significantly increased the number of artifact-free frequencies in the frequency domain. This performance surpasses that of a more traditional independent component analysis methodology, while retaining a reduced complexity and increased computational efficiency.

The RxHL study: community-responsive research to explore barriers to medication adherence.

This study aims to contribute to the development of community-responsive research approaches by describing the research methods used in the RxHL study and the interprofessional and community-based collaboration that produced them. The mixed-method RxHL study was developed in close consultation with staff and providers at our research site, a federally qualified health center in Springfield, MA. We utilized quantitative methods including chart review, manual pill counts and self-report surveys to assess factors associated with medication adherence in a diverse population of low-income patients with chronic disease. We triangulated these results with findings from qualitative methods that included in-depth interviews, home visits and chronic disease diaries. We used the constant comparison method and interdisciplinary, participatory team meetings to integrate quantitative and qualitative findings. A community-responsive approach facilitated the recruitment and retention of a diverse sample of patients. Self-report surveys revealed the widespread scope of barriers to care such as medication costs and transportation, and limited health literacy among diverse groups. Qualitative research methods offered a deeper understanding of the social and environmental contexts in which medication adherence takes place. Prioritizing the needs of community partners and research participants facilitates rigorous data collection in clinical settings with maximum participation from community partners.

A benchtop system to assess the feasibility of a fully independent and implantable brain-machine interface.

OBJECTIVE: State-of-the-art invasive brain-machine interfaces (BMIs) have shown significant promise, but rely on external electronics and wired connections between the brain and these external components. This configuration presents health risks and limits practical use. These limitations can be addressed by designing a fully implantable BMI similar to existing FDA-approved implantable devices. Here, a prototype BMI system whose size and power consumption are comparable to those of fully implantable medical devices was designed and implemented, and its performance was tested at the benchtop and bedside. APPROACH: A prototype of a fully implantable BMI system was designed and implemented as a miniaturized embedded system. This benchtop analogue was tested in its ability to acquire signals, train a decoder, perform online decoding, wirelessly control external devices, and operate independently on battery. Furthermore, performance metrics such as power consumption were benchmarked. MAIN RESULTS: An analogue of a fully implantable BMI was fabricated with a miniaturized form factor. A patient undergoing epilepsy surgery evaluation with an electrocorticogram (ECoG) grid implanted over the primary motor cortex was recruited to operate the system. Seven online runs were performed with an average binary state decoding accuracy of 87.0% (lag optimized, or 85.0% at fixed latency). The system was powered by a wirelessly rechargeable battery, consumed ∼150 mW, and operated for >60 h on a single battery cycle. SIGNIFICANCE: The BMI analogue achieved immediate and accurate decoding of ECoG signals underlying hand movements. A wirelessly rechargeable battery and other supporting functions allowed the system to function independently. In addition to the small footprint and acceptable power and heat dissipation, these results suggest that fully implantable BMI systems are feasible.

Changes in Food Insecurity and Smoking Status over Time: Analysis of the 2003 and 2015 Panel Study of Income Dynamics.

PURPOSE: To examine whether food insecurity longitudinally affects smoking status. DESIGN: Population-based prospective study. SETTING: Data from the 2003 and 2015 Panel Study of Income Dynamics (PSID). PARTICIPANTS: Four thousand five hundred sixty-three adults who were smokers and nonsmokers, participating in the 2003 (current study baseline) and 2015 (current study follow-up) waves of PSID. MEASURES: Based on self-reported smoking status at baseline and follow-up, respondents were categorized as continued smoking, stopped smoking, started smoking, and continued nonsmoking. Similarly, respondents were categorized as stayed food secure, stayed food insecure, became food insecure, and became food secure based on responses to the Food Security Survey at baseline and follow-up. ANALYSIS: Two logistic regression analyses to examine (1) among smokers at baseline the odds of stopping versus continuing smoking by follow-up and (2) among nonsmokers at baseline the odds of starting versus continuing nonsmoking by follow-up. In both models, change in food insecurity status was the primary independent variable, controlling for demographics including poverty. RESULTS: Among smokers at baseline, becoming food insecure (vs staying food secure) was independently associated with lower likelihood of stopping smoking by follow-up (odds ratio [OR] = 0.66). Among nonsmokers at baseline, becoming food insecure (vs staying food secure) was independently associated with higher likelihood of starting smoking by follow-up (OR = 3.77). CONCLUSIONS: Food insecurity is a risk factor for smoking, which has significant implications for developing interventions to reduce smoking prevalence, especially among low-income groups.

Characterization of Stimulation Artifact Behavior in Simultaneous Electrocorticography Grid Stimulation and Recording.

Bi-directional brain-computer interfaces (BCIs) require simultaneous stimulation and recording to achieve closed-loop operation. It is therefore important that the interface be able to distinguish between neural signals of interest and stimulation artifacts. Current bi-directional BCIs address this problem by temporally multiplexing stimulation and recording. This approach, however, is suboptimal in many BCI applications. Alternative artifact mitigation methods can be devised by investigating the mechanics of artifact propagation. To characterize stimulation artifact behaviors, we collected and analyzed electrocorticography (ECoG) data from eloquent cortex mapping. Ratcheting and phase-locking of stimulation artifacts were observed, as well as dipole-like properties. Artifacts as large as ±1,100 µV appeared as far as 15-37 mm away from the stimulating channel when stimulating at 10 mA. Analysis also showed that the majority of the artifact power was concentrated at the stimulation pulse train frequency (50 Hz) and its super-harmonics (100, 150, 200 Hz). Lower frequencies (0-32 Hz) experienced minimal artifact contamination. These findings could inform the design of future bi-directional ECoG-based BCIs.

The pharmaceutical regulation of chronic disease among the U.S. urban poor: an ethnographic study of accountability.

The Massachusetts experience of health care reform before the Affordable Care Act of 2010 reveals a moral economy of care in which expanded access was met by neoliberal demands for accountability and cost control. Publicly-subsidized health insurance programs in the U.S. are deeply concerned with managing and regulating low-income residents' access to and coverage for medications. By focusing our attention on the new forms of social relations invoked by specific techniques of governing, analyses of accountability can help us understand the ways in which subjectivities are shaped through their encounters with overarching social and economic structures. This paper presents qualitative findings from a four-year, prospective study that combined two waves of survey and chart-based data collection with four qualitative methods. Medicaid patients are made accountable to their medication regimens as they must track their supply and obtain refills promptly; regular blood tests carried out by health care providers verify their adherence. Both patients and their physicians are subject to cost savings measures such as changing lists of covered medications. Finally, patients struggle to pay ever-increasing out-of-pocket costs for their medications, expenses which may keep patients from taking their medications as prescribed. The fraught relationship between trust, accountability and verification finds emphatic expression in the moral economy of health care, where the vulnerability of the sick and their hope for a cure confront policies designed to hold down costs.

Electrocorticographic Encoding of Human Gait in the Leg Primary Motor Cortex.

While prior noninvasive (e.g., electroencephalographic) studies suggest that the human primary motor cortex (M1) is active during gait processes, the limitations of noninvasive recordings make it impossible to determine whether M1 is involved in high-level motor control (e.g., obstacle avoidance, walking speed), low-level motor control (e.g., coordinated muscle activation), or only nonmotor processes (e.g., integrating/relaying sensory information). This study represents the first invasive electroneurophysiological characterization of the human leg M1 during walking. Two subjects with an electrocorticographic grid over the interhemispheric M1 area were recruited. Both exhibited generalized γ-band (40-200 Hz) synchronization across M1 during treadmill walking, as well as periodic γ-band changes within each stride (across multiple walking speeds). Additionally, these changes appeared to be of motor, rather than sensory, origin. However, M1 activity during walking shared few features with M1 activity during individual leg muscle movements, and was not highly correlated with lower limb trajectories on a single channel basis. These findings suggest that M1 primarily encodes high-level gait motor control (i.e., walking duration and speed) instead of the low-level patterns of leg muscle activation or movement trajectories. Therefore, M1 likely interacts with subcortical/spinal networks, which are responsible for low-level motor control, to produce normal human walking.

Characterization of electrocorticogram high-gamma signal in response to varying upper extremity movement velocity.

The mechanism by which the human primary motor cortex (M1) encodes upper extremity movement kinematics is not fully understood. For example, human electrocorticogram (ECoG) signals have been shown to modulate with upper extremity movements; however, this relationship has not been explicitly characterized. To address this issue, we recorded high-density ECoG signals from patients undergoing epilepsy surgery evaluation as they performed elementary upper extremity movements while systematically varying movement speed and duration. Specifically, subjects performed intermittent pincer grasp/release, elbow flexion/extension, and shoulder flexion/extension at slow, moderate, and fast speeds. In all movements, bursts of power in the high-[Formula: see text] band (80-160 Hz) were observed in M1. In addition, the amplitude of these power bursts and the area of M1 with elevated high-[Formula: see text] activity were directly proportional to the movement speed. Likewise, the duration of elevated high-[Formula: see text] activity increased with movement duration. Based on linear regression, M1 high-[Formula: see text] power amplitude and duration covaried with movement speed and duration, respectively, with an average [Formula: see text] of [Formula: see text] and [Formula: see text]. These findings indicate that the encoding of upper extremity movement speed by M1 high-[Formula: see text] activity is primarily linear. Also, the fact that this activity remained elevated throughout a movement suggests that M1 does not merely generate transient instructions for a specific movement duration, but instead is responsible for the entirety of the movement. Finally, the spatial distribution of high-[Formula: see text] activity suggests the presence of a recruitment phenomenon in which higher speeds or increased muscle activity involve activation of larger M1 areas.

Comparison of decoding resolution of standard and high-density electrocorticogram electrodes.

OBJECTIVE: Electrocorticography (ECoG)-based brain-computer interface (BCI) is a promising platform for controlling arm prostheses. To restore functional independence, a BCI must be able to control arm prostheses along at least six degrees-of-freedoms (DOFs). Prior studies suggest that standard ECoG grids may be insufficient to decode multi-DOF arm movements. This study compared the ability of standard and high-density (HD) ECoG grids to decode the presence/absence of six elementary arm movements and the type of movement performed. APPROACH: Three subjects implanted with standard grids (4 mm diameter, 10 mm spacing) and three with HD grids (2 mm diameter, 4 mm spacing) had ECoG signals recorded while performing the following movements: (1) pincer grasp/release, (2) wrist flexion/extension, (3) pronation/supination, (4) elbow flexion/extension, (5) shoulder internal/external rotation, and (6) shoulder forward flexion/extension. Data from the primary motor cortex were used to train a state decoder to detect the presence/absence of movement, and a six-class decoder to distinguish between these movements. MAIN RESULTS: The average performances of the state decoders trained on HD ECoG data were superior (p = 3.05 × 10(-5)) to those of their standard grid counterparts across all combinations of the µ, ß, low-γ, and high-γ frequency bands. The average best decoding error for HD grids was 2.6%, compared to 8.5% of standard grids (chance 50%). The movement decoders trained on HD ECoG data were superior (p = 3.05 × 10(-5)) to those based on standard ECoG across all band combinations. The average best decoding errors of 11.9% and 33.1% were obtained for HD and standard grids, respectively (chance error 83.3%). These improvements can be attributed to higher electrode density and signal quality of HD grids. SIGNIFICANCE: Commonly used ECoG grids are inadequate for multi-DOF BCI arm prostheses. The performance gains by HD grids may eventually lead to independence-restoring BCI arm prosthesis.

Breast self-examination beliefs and practices, ethnicity, and health literacy: Implications for health education to reduce disparities.

OBJECTIVE: This study aimed to quantitatively and qualitatively examine breast cancer screening practices, including breast self-examination (BSE), and health literacy among patients with chronic disease. DESIGN: A prospective, multi-method study conducted with a targeted purposive sample of 297 patients with diabetes and/or hypertension from four ethnic groups (Latino, Vietnamese, African American, White-American) at an urban community health center. SETTING: A federally qualified health center in Western Massachusetts. METHODS: In our four-year study, 297 participants completed cancer knowledge, beliefs, attitudes and screening utilization scales and measures of health literacy. In addition to survey data collection, we conducted in-depth interviews, focus groups, home visits, and chronic disease diaries (n=71). RESULTS: In focus groups, African American, Vietnamese and Latina participants offered interviewers an unprompted demonstration of BSE, reported regular BSE use at particular times of the month, and shared positive feelings about the screening method. In a sample where approximately 93% of women have had a mammogram, many also had performed BSE (85.2%). Women with adequate health literacy were more likely than those with inadequate health literacy to rely on it. Despite being positively inclined toward BSE, Vietnamese women, who had the lowest health literacy scores in our sample, were less likely to perform BSE regularly. CONCLUSIONS: BSE seemed to be an appealing self-care practice for many women in our study, but we conclude that proper BSE practices may not be reinforced equally across ethnic groups and among patients with low health literacy.

Extracting kinetic information from human motor cortical signals.

Brain machine interfaces (BMIs) have the potential to provide intuitive control of neuroprostheses to restore grasp to patients with paralyzed or amputated upper limbs. For these neuroprostheses to function, the ability to accurately control grasp force is critical. Grasp force can be decoded from neuronal spikes in monkeys, and hand kinematics can be decoded using electrocorticogram (ECoG) signals recorded from the surface of the human motor cortex. We hypothesized that kinetic information about grasping could also be extracted from ECoG, and sought to decode continuously-graded grasp force. In this study, we decoded isometric pinch force with high accuracy from ECoG in 10 human subjects. The predicted signals explained from 22% to 88% (60 ± 6%, mean ± SE) of the variance in the actual force generated. We also decoded muscle activity in the finger flexors, with similar accuracy to force decoding. We found that high gamma band and time domain features of the ECoG signal were most informative about kinetics, similar to our previous findings with intracortical LFPs. In addition, we found that peak cortical representations of force applied by the index and little fingers were separated by only about 4mm. Thus, ECoG can be used to decode not only kinematics, but also kinetics of movement. This is an important step toward restoring intuitively-controlled grasp to impaired patients.

Electrocorticogram encoding of upper extremity movement duration.

Electrocorticogram (ECoG) is a promising long-term signal acquisition platform for brain-computer interface (BCI) systems such as upper extremity prostheses. Several studies have demonstrated decoding of arm and finger trajectories from ECoG high-gamma band (80-160 Hz) signals. In this study, we systematically vary the velocity of three elementary movement types (pincer grasp, elbow and shoulder flexion/extension) to test whether the high-gamma band encodes for the entirety of the movements, or merely the movement onset. To this end, linear regression models were created for the durations and amplitudes of high-gamma power bursts and velocity deflections. One subject with 8×8 high-density ECoG grid (4 mm center-to-center electrode spacing) participated in the experiment. The results of the regression models indicated that the power burst durations varied directly with the movement durations (e.g. R(2)=0.71 and slope=1.0 s/s for elbow). The persistence of power bursts for the duration of the movement suggests that the primary motor cortex (M1) is likely active for the entire duration of a movement, instead of providing a marker for the movement onset. On the other hand, the amplitudes were less co-varied. Furthermore, the electrodes of maximum R(2) conformed to somatotopic arrangement of the brain. Also, electrodes responsible for flexion and extension movements could be resolved on the high-density grid. In summary, these findings suggest that M1 may be directly responsible for activating the individual muscle motor units, and future BCI may be able to utilize them for better control of prostheses.

Sensitivity and specificity of upper extremity movements decoded from electrocorticogram.

Electrocorticogram (ECoG)-based brain computer interfaces (BCI) can potentially be used for control of arm prostheses. Restoring independent function to BCI users with such a system will likely require control of many degrees-of-freedom (DOF). However, our ability to decode many-DOF arm movements from ECoG signals has not been thoroughly tested. To this end, we conducted a comprehensive study of the ECoG signals underlying 6 elementary upper extremity movements. Two subjects undergoing ECoG electrode grid implantation for epilepsy surgery evaluation participated in the study. For each task, their data were analyzed to design a decoding model to classify ECoG as idling or movement. The decoding models were found to be highly sensitive in detecting movement, but not specific in distinguishing between different movement types. Since sensitivity and specificity must be traded-off, these results imply that conventional ECoG grids may not provide sufficient resolution for decoding many-DOF upper extremity movements.