Jane E Huggins

• PhD
• Research Associate Professor at University of Michigan

The Brain-Computer Interface (BCI) was envisioned as an assistive technology option for people with severe movement impairments. The traditional synchronous event-related potential (ERP) BCI design uses a fixed communication speed and is vulnerable to variations in attention. Recent ERP BCI designs have added asynchronous features, including absten...

The brain-computer interface (BCI) enables individuals with severe physical impairments to communicate with the world. BCIs offer computational neuroscience opportunities and challenges in converting real-time brain activities to computer commands and are typically framed as a classification problem. This article focuses on the P300 BCI that uses t...

Objective: This study examined the effect of individualized electroencephalogram (EEG) electrode location selection for non-invasive P300-design brain-computer interfaces (BCIs) in people with varying severity of cerebral palsy (CP). Approach: A forward selection algorithm was used to select the best performing 8 electrodes (of an available 32) to...

Brain-computer interfaces (BCIs) have been successfully used by adults, but little information is available on BCI use by children, especially children with severe multiple impairments who may need technology to facilitate communication. Here we discuss the challenges of using non-invasive BCI with children, especially children who do not have anot...

Objective To examine measurement agreement between a vocabulary test that is administered in the standardized manner and a version that is administered with a brain-computer interface (BCI).Method The sample was comprised of 21 participants, ages 9–27, mean age 16.7 (5.4) years, 61.9% male, including 10 with congenital spastic cerebral palsy (CP),...

A brain-computer interface (BCI) is a system that translates brain activity into commands to operate technology. A common design for an electroencephalogram (EEG) BCI relies on the classification of the P300 event-related potential (ERP), which is a response elicited by the rare occurrence of target stimuli among common non-target stimuli. Few exis...

The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering the breadth of topics in BCI (also called brain-machine interface) research. Some workshops provided detailed examinations of methods, hardware, o...

A Brain-Computer Interface (BCI) is a device that interprets brain activity to help people with disabilities communicate. The P300 ERP-based BCI speller displays a series of events on the screen and searches the elicited electroencephalogram (EEG) data for target P300 event-related potential (ERP) responses among a series of non-target events. The...

Advancements in novel neurotechnologies, such as brain computer interfaces (BCI) and neuromodulatory devices such as deep brain stimulators (DBS), will have profound implications for society and human rights. While these technologies are improving the diagnosis and treatment of mental and neurological diseases, they can also alter individual agency...

Background Brain‐computer interface (BCI) technology is an emerging access method to augmentative and alternative communication (AAC) devices. Objectives To identify, in the early stages of research and development, the perceptions and considerations of inter‐professional practice (IPP) team members regarding features and functions for an AAC‐BCI...

Brain-Computer Interfaces (BCIs) have been used to restore communication and control to people with severe paralysis. However, noninvasive BCIs based on electroencephalogram (EEG) are particularly vulnerable to noise artifacts. These artifacts, including electro-oculogram (EOG), can be orders of magnitude larger than the signal to be detected. Many...

The purpose of this study was to evaluate the feasibility of a novel non-invasive P300-based brain computer interface (BCI) mouse emulation device (MED), along with a commercial head-mouse among experienced head-mouse users with cervical spinal cord injury (SCI). The setting was a controlled experimental set-up. Feasibility was shown for the P300-B...

The Seventh International Brain-Computer Interface (BCI) Meeting was held May 21-25th, 2018 at the Asilomar Conference Grounds, Pacific Grove, California, United States. The interactive nature of this conference was embodied by 25 workshops covering topics in BCI (also called brain-machine interface) research. Workshops covered foundational topics...

Much brain-computer interface (BCI) research is intended to benefit people with disabilities (PWD), though they are rarely included as study participants. When included, a range of clinical and non-clinical descriptions are used leading to difficulty interpreting and replicating results. We examined trends in inclusion and description of study part...

Brain-computer Interface (BCI) research is rapidly expanding, and it engages domains of human experience that many find central to our current understanding of ourselves. Ethical principles or guidelines can provide researchers with tools to engage in ethical reflection and to address practical problems in research. Though researchers have called f...

Event-related potentials (ERPs) are the brain response directly related to specific events or stimuli. The P300 ERP is a positive deflection nominally 300ms post-stimulus that is related to mental decision making processes and also used in P300-based speller systems. Single-trial estimation of P300 responses will help to understand the underlying c...

In this investigation, we demonstrate a non-invasive P300-design brain-computer interface (BCI) controlling a robotic quadcopter (Bepop Parrot) for object retrieval in a 3D space. The single subject launched the quadcopter and maneuvered in straight lines to retrieve an object fitted with a metallic tape. By integrating P300 BCI with Android Studio...

A method to estimate P300 ERPs in single trials, as well as latencies and amplitudes.

Brain–computer interfaces (BCIs) are topics of great interest to people who need augmentative and alternative communication. Although media reports focus on the promise of BCI to provide communication without physical movement, such reports often contain few details to critically evaluate whether BCIs are yet sufficiently developed for real-world c...

Performance assessment has a pivotal role in the development of BCI systems and algorithms. A large number of performance-measuring metrics exist in the literature, and the choice of best metric may be difficult for researchers. The main objective of this chapter is to demonstrate different performance assessment criteria as well as to report the m...

Objective. Typically, clinical measures of cognition require motor or speech responses. Thus, a significant percentage of people with disabilities are not able to complete standardized assessments. This situation could be resolved by employing a more accessible test administration method, such as a brain–computer interface (BCI). A BCI can circumve...

Artificial intelligence and brain–computer interfaces must respect and preserve people's privacy, identity, agency and equality, say Rafael Yuste, Sara Goering and colleagues.

Brain Computer Interfaces (BCIs) offer restoration of communication to those with the most severe movement impairments, but performance is not yet ideal. Previous work has demonstrated that latency jitter, the variation in timing of the brain responses, plays a critical role in determining BCI performance. In this study, we used Classifier-Based La...

The Sixth International Brain–Computer Interface (BCI) Meeting was held 30 May–3 June 2016 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 28 workshops covering topics in BCI and brain–machine interface research. Topics included BCI for specific populations or applications, advancing BCI research through...

Foreword The International Brain-Computer Interface (BCI) Meeting Series occupies a unique place among conferences for BCI research by bringing together researchers and stakeholders from diverse disciplines. Neurologists, computer scientists, rehabilitation engineers, physicians, sensor engineers, psychologists, speech-language pathologists, ethici...

Brain-computer interfaces (BCIs) are intended to provide independent communication for those with the most severe physical impairments. However, development and testing of BCIs is typically conducted with copy-spelling of provided text, which models only a small portion of a functional communication task. This study was designed to determine how BC...

A non-invasive brain-computer interface (BCI)-adapted version of the Peabody Picture Vocabulary Test - 4th Edition (PPVT-IV) was created with the overall goal of enabling test participation by people unable to make the speech or movement responses required for the unmodified test. The BCI-adapted PPVT-IV used custom algorithms to wait for the parti...

More than 300 researchers gathered at the 2013 International Brain-Computer Interface (BCI) Meeting to discuss current practice and future goals for BCI research and development. The authors organized the Virtual Users' Forum at the meeting to provide the BCI community with feedback from users. We report on the Virtual Users' Forum, including initi...

A formal definition of brain-computer interface (BCI) is as follows: a system that acquires brain signal activity and translates it into an output that can replace, restore, enhance, supplement, or improve the existing brain signal, which can, in turn, modify or change ongoing interactions between the brain and its internal or external environment....

To identify perceptions among people with spinal cord injury (SCI) of the priorities for brain-computer interface (BCI) applications and design features along with the time investment and risk acceptable to obtain a BCI. Survey. Research registry participants surveyed via telephone and BCI usage study participants surveyed in person before BCI use....

Assistive technology control interface theory describes interface activation and interface deactivation as distinct properties of any control interface. Separating control of activation and deactivation allows precise timing of the duration of the activation. Objective. We propose a novel P300 brain–computer interface (BCI) functionality with separ...

Brain–computer interfaces (BCIs), also known as brain–machine interfaces (BMIs), translate brain activity into new outputs that replace, restore, enhance, supplement or improve natural brain outputs. BCI research and development has grown rapidly for the past two decades. It is beginning to provide useful communication and control capacities to peo...

Objective. Brain–computer interfaces (BCIs) have the potential to be valuable clinical tools. However, the varied nature of BCIs, combined with the large number of laboratories participating in BCI research, makes uniform performance reporting difficult. To address this situation, we present a tutorial on performance measurement in BCI research. Ap...

The Fifth International Brain-Computer Interface (BCI) Meeting met on 3–7 June 2013 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 19 workshops covering topics in brain-computer interface and brain-machine interface research. Topics included translation of BCIs into clinical use, standardization and cert...

Purpose: An electroencephalography (EEG)-based P300 speller is a type of brain-computer interface (BCI) that uses EEG to allow a user to select characters without physical movement. In general, using fewer electrodes for such a system makes it easier to set up and less expensive. This study addresses the question of electrode selection for EEG-bas...

A large number of incommensurable metrics are currently used to report the performance of brain-computer interfaces (BCI) used for augmentative and alterative communication (AAC). The lack of standard metrics precludes the comparison of different BCI-based AAC systems, hindering rapid growth and development of this technology. This paper presents a...

Purpose: To determine if a brain-computer interface (BCI) could be used as a plug-and-play input device to operate commercial assistive technology (AT), and to quantify the performance impact of such operation. Method: Using a hardware device designed in our lab, participants (11 with amyotrophic lateral sclerosis, 22 controls) were asked to ope...

Amyotrophic lateral sclerosis (ALS) is a disorder associated primarily with the degeneration of the motor system. More recently, functional connectivity studies have demonstrated potentially adaptive changes in ALS brain organization, but disease-related changes in cortical communication remain unknown. We recruited individuals with ALS and age-mat...

Objective. Brain–computer interfaces (BCIs) that detect event-related potentials (ERPs) rely on classification schemes that are vulnerable to latency jitter, a phenomenon known to occur with ERPs such as the P300 response. The objective of this work was to investigate the role that latency jitter plays in BCI classification. Approach. We developed...

Unlabelled: Brain-computer interfaces (BCI) are designed to enable individuals with severe motor impairments such as amyotrophic lateral sclerosis (ALS) to communicate and control their environment. A focus group was conducted with individuals with ALS (n=8) and their caregivers (n=9) to determine the barriers to and mediators of BCI acceptance in...

Many people with disabilities already use assistive technology (AT) to provide accessible interfaces with commercial devices that were not designed with a disabled user in mind. This chapter addresses brain-computer interface (BCI) development and implementation as an exciting and potentially important new AT area. It has six major sections. The fi...

Brain-computer interfaces (BCIs) may serve as augmentative communication systems for individuals with amyotrophic lateral sclerosis (ALS) who have lost the ability to speak and move their limbs. While BCI technology has potential value for these individuals, BCI research has emphasized issues such as algorithm development and signal processing tech...

While brain-computer interfaces (BCIs) are a promising alternative access pathway for individuals with severe motor impairments, many BCI systems are designed as stand-alone communication and control systems, rather than as interfaces to existing systems built for these purposes. An individual communication and control system may be powerful or fle...

Universal design principles advocate inclusion of end users in every design stage, including research and development. Brain-computer interfaces (BCIs) have long been described as potential tools to enable people with amyotrophic lateral sclerosis (ALS) to operate technology without moving. Therefore the objective of the current study is to determi...

Assistive devices are prescribed for amyotrophic lateral sclerosis (ALS) patients with motor deficits, but little is known about their perceived benefit. Therefore, we assessed ALS patients' satisfaction with commonly prescribed devices. A telephone survey of 63 ALS patients from a single multidisciplinary clinic was conducted to assess the frequen...

This chapter provides an introduction to electrocorticogram (ECoG) as a signal source for brain–computer interfaces (BCIs). I first define ECoG, examine its advantages and disadvantages, and outline factors affecting successful ECoG experiments for BCI. Past and present BCI projects that utilize ECoG and have published results through early 2008 ar...

The Multi-purpose BCI Output Device (MBOD), emulates a USB keyboard and/or mouse, as well as producing switch closures, thus allowing BCI2000 to output to various assistive technology (AT) devices. The MBOD should allow researchers easy access to the many advantages of commercial AT in addition to providing continuity of service for patients. The s...

The latest research in the development of technologies that will allow humans to communicate, using brain signals only, with computers, wheelchairs, prostheses, and other devices. Interest in developing an effective communication interface connecting the human brain and a computer has grown rapidly over the past decade. The brain-computer interface...

The latest research in the development of technologies that will allow humans to communicate, using brain signals only, with computers, wheelchairs, prostheses, and other devices. Interest in developing an effective communication interface connecting the human brain and a computer has grown rapidly over the past decade. The brain-computer interface...

19.1 Abstract To analyze the performance of BCI systems, some evaluation criteria must be applied. The most popular is accuracy or error rate. Because of some strict prerequisites, accuracy is not always a suitable criterion, and other evaluation criteria have been proposed. This chapter provides an overview of evaluation criteria used in BCI resea...

The University of Michigan Direct Brain Interface (UM-DBI) project seeks to detect voluntarily produced electrocortical activity (ECoG) related to actual or imagined movements in humans as the basis for a DBI. In past work we have used cross-correlation based template matching (CCTM) as the method for detecting event-related potentials (ERPs). That...

Almost all brain-computer interfaces (BCIs) ignore information related to the phase coupling between electroencephalogram (EEG) or electrocorticogram (ECoG) recordings from different electrodes. This paper investigates whether additional information can be found when calculating the amount of synchronization between two electrode channels by using...

Highly accurate asynchronous detection of movement related patterns in individual electrocorticogram channels has been shown using detection based on either event-related potentials (ERPs) or event-related desynchronization and synchronization (ERD/ERS). A method using wavelet-packet features selected with a genetic algorithm was proposed to simult...

A brain computer interface (BCI) is an assistive device that recognizes voluntary commands from the brain and triggers appropriate external responses, without requiring physical movement. The ultimate goal of such an interface is to provide effective communication without using the normal neuromuscular output pathways of the brain but by accepting...

Adaptive autoregressive parameters and a linear classifier were used to detect movement related desynchronization and synchronization patterns in single-channel electrocorticogram (ECoG) obtained from implanted electrode grids. The best classification accuracies found had more than 90% hits and less than 10% false positives. The findings show that...

To study the spatiotemporal pattern of event-related desynchronization (ERD) and event-related synchronization (ERS) in electrocorticographic (ECoG) data with closely spaced electrodes. Four patients with epilepsy performed self-paced hand movements. The ERD/ERS was quantified and displayed in the form of time-frequency maps. In all subjects, a sig...

A direct brain interface (DBI) based on the detection of event-related potentials (ERPs) in human electrocorticogram (ECoG) is under development. Accurate detection has been demonstrated with this approach (near 100% on a few channels) using a single-channel cross-correlation template matching (CCTM) method. Several opportunities for improved detec...

Wavelet packet analysis and a genetic algorithm were used to detect movement-related patterns in single channel electrocorticogram (ECoG). Detection accuracies of more than 90% hits and less than 10% false positives were found. The findings show that the detection of movement-related patterns in ECoG data can be used to reliably provide switch cont...

The aim of the present study was to investigate the most significant frequency components in electrocorticogram (ECoG) recordings in order to operate a brain computer interface (BCI). For this purpose the time-frequency ERD/ERS map and the distinction sensitive learning vector quantization (DSLVQ) are applied to ECoG from three subjects, recorded d...

The aim of the present study was to investigate the most significant frequency components in electrocorticogram (ECoG) recordings in order to operate a brain computer interface (BCI). For this purpose the time-frequency ERD/ERS map and the distinction sensitive learning vector quantization (DSLVQ) are applied to ECoG from three subjects, recorded d...

Analysis of event-related desynchronization (ERD) and event-related synchronization (ERS) often requires the investigation of diverse frequency bands. Such analysis can be difficult, especially when using multichannel data. Therefore, an effective method for the visualization of event-related changes in oscillatory brain activity is required. A boo...

Our goal is to develop a direct brain interface (DBI) that will provide communication and environmental control to persons who are "locked-in" (or nearly so) as a consequence of brainstem stroke, amyotrophic lateral sclerosis (ALS), or other etiologies. Previously we demonstrated that templates constructed from trigger averaged event-related potent...

assuming "colored" noise, it can be shown that the optimal detector depends on the covariance of the time samples. The problem with this model is that, because the ERP may last several seconds, we can never expect to have enough event observations from a given subject to estimate the full covariance matrix. Thus, there is no way to implement the op...

Decubitous ulcers (“pressure sores”) are a significant concern for people using wheelchairs. In fact, results published by the University of Kansas [1] indicate that over half of those using wheelchairs will develop a pressure sore at some point. This susceptibility is due to the conditions under which these ulcers develop: shear stress and pressur...

Cross-correlation between a trigger-averaged event-related potential (ERP) template and continuous electrocorticogram was used to detect movement-related ERP's. The accuracy of ERP detection for the five best subjects (of 17 studied), had hit percentages >90% and false positive percentages <10%. These cases were considered appropriate for operation...

This study reports on the first step in the development of a direct brain interface based on the identification of event-related potentials (ERPs) from an electrocorticogram obtained from the surface of the cortex. Ten epilepsy surgery patients, undergoing monitoring with subdural electrode strips and grid arrays, participated in this study. Electr...

The study presented here is part of an ongoing effort to develop a direct brain interface based on detection of event-related potentials (ERPs). In a study presented in a companion article, averaged ERP templates were identified from electrocorticograms recorded during repetition of voluntary motor actions. Here the authors report on the detection...

Electrocorticogram (ECoG) from neighboring electrode locations contains a certain amount of redundancy. In order to take advantage of this redundancy to improve event-related potential (ERP) detection accuracy, four methods of multi-channel combination were tested. The best performance was achieved with the cross-correlelogram averaging method, whi...

A high level, interactive tool for the acquisition and processing of human event related potentials (ERPs) is presented. The software/hardware combination features on-line triggered averaging, real time quality analysis, and feedback to the subject for training purposes. Additionally, the instrument can be used as a prototype “Direct Brain Interfac...

ERPs) is presented. The software/hardware combination features on-line triggered averaging, real time quality analysis, and feedback to the subject for training purposes. Additionally, the instrument can be used as a prototype “Direct Brain Interface” (DBI) for rehabilitation applications. Index Terms: ERP, cortical, brain interface, feedback

Signal-to-noise ratio (SNR) measures have long been used to examine the quality of evoked potential recordings. Özdamar and Delgado (1996) derived an energy-based SNR measure and applied it to auditory brainstem responses. Preliminary evidence is presented that this running SNR estimate can also be used to identify voluntary, motor-related, cortica...

A direct brain interface for control of assistive technologies is being developed based on intracranial detection of movement-related potentials. Subjects for this research are patients who have electrodes implanted for monitoring purposes prior to epilepsy surgery. Triggered averaging is used to create event-related potential (ERP) templates relat...

The University of Michigan Direct Brain Interface (UM-DBI) project seeks to detect voluntarily produced electrocortical activity (ECoG) related to actual or imagined movements in humans as the basis for a DBI. In past work we have used cross-correlation based template matching (CCTM) to detect event-related potentials (ERPs). This paper focuses on...

While wheelchairs have been controlled by a brain-computer interface (BCI) (e.g. [1-3]), systems that allow the operation of a subject's own wheelchair are not available. Control of a wheelchair-mounted tilt-in-space seating system, however, can provide important benefits to people with amyotrophic lateral sclerosis (ALS), while avoiding many of th...