Glossary

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F-Droid

A catalogue and package repository for free and open-source Android applications, used as an alternative to Google Play, with every app built and signed from publicly auditable source code. Accessibility researchers frequently use F-Droid as a target ecosystem for studies and…

F-measure(also: F-score, F1 Score)

A metric that combines correctness (precision) and sensitivity (recall) into a single balanced score, calculated as the harmonic mean of the two values. In accessibility evaluation research, the F-measure provides a single number representing the overall effectiveness of an…

FAIR Principles(also: FAIR Data Principles, Findable Accessible Interoperable Reusable)

The FAIR Principles are a set of guidelines for making digital data and resources Findable, Accessible, Interoperable, and Reusable. Developed by an international consortium and published in 2016, they are widely adopted in research, libraries, and cultural heritage…

FATE Framework(also: FATE, Fairness Accountability Transparency Ethics)

An ethical framework for evaluating AI and machine learning systems across four dimensions: Fairness (ensuring equitable treatment and outcomes across different groups), Accountability (establishing responsibility for system decisions and impacts), Transparency (making system…

FERPA(also: Family Educational Rights and Privacy Act, Buckley Amendment)

A United States federal law enacted in 1974 that protects the privacy of student education records. FERPA gives parents and eligible students (those over 18 or attending postsecondary education) rights to access, review, and request corrections to their educational records. The…

FOSTA-SESTA(also: Allow States and Victims to Fight Online Sex Trafficking Act, Stop Enabling Sex Traffickers Act)

U.S. federal legislation (2018) that amended Section 230 of the Communications Decency Act to make online platforms liable for user content that facilitates sex trafficking. While intended to combat trafficking, the laws have had significant negative consequences for disabled…

FPGA(also: Field-Programmable Gate Array)

An integrated circuit that can be configured by the user after manufacturing to implement custom digital logic. FPGAs contain an array of programmable logic blocks and interconnects that can be reprogrammed to perform different functions. In assistive technology, FPGAs enable…

Fabrication(also: AI Fabrication, Confabulation)

An AI error where the model generates content that does not exist in the input, such as describing objects not present in an image, inventing text that does not appear in a document, or creating details that are entirely fictional. Fabrication is distinct from misinterpretation…

Face Detection(also: Face Recognition, Facial Detection)

A computer vision technology that identifies and locates human faces within digital images or video frames, typically providing bounding box coordinates around each detected face. Face detection serves as the foundation for more advanced tasks like face recognition (identifying…

Face Recognition(also: Facial Recognition, Face Detection)

A technology that uses computer vision and machine learning to identify or verify a person by analysing their facial features from images or video. In accessibility contexts, face recognition has significant potential as an assistive tool for blind and deafblind people, enabling…

Face Swap(also: Face Transformation, Face Replacement)

A technology that replaces the face of a person in a video or image with a different face while attempting to preserve the original person's facial expressions, head movements, and lip synchronization. In the context of accessibility, face swap technology has potential…

Face Tracking(also: Facial Tracking, Face Detection and Tracking)

A computer vision technology that detects and follows the position and movement of a user's face in real time using a camera or depth sensor. In accessibility, face tracking enables hands-free computer interaction for people with motor disabilities who cannot use traditional…

FaceReader(also: Noldus FaceReader)

A commercial facial-expression recognition software (developed by Noldus) that uses computer vision and deep learning to automatically classify faces into basic emotions (neutral, happy, sad, angry, surprised, scared, disgusted) and to estimate emotional valence and arousal in…

Faceted Navigation(also: Faceted Search, Faceted Browsing, Faceted Filtering)

A navigation technique that allows users to filter and explore content along multiple dimensions or categories simultaneously, such as by topic, sentiment, date, or rating. In accessibility contexts, faceted navigation can significantly improve the efficiency of information…

Facial Action Coding System(also: FACS)

A comprehensive, anatomically based system for describing all visually discernible facial movements, originally developed by Paul Ekman and Wallace Friesen in 1977. FACS decomposes facial expressions into individual components called Action Units (AUs), each corresponding to the…

Facial Action Unit(also: Action Unit, AU, FACS Action Unit)

A component of the Facial Action Coding System (FACS) that represents a specific movement or position of facial muscles. Each action unit corresponds to a distinct facial movement, such as raising the inner eyebrow (AU1) or pulling the lip corner (AU12 for smiling). In…

Facial Affect(also: Facial Expression of Emotion, Emotional Facial Expression)

The display of emotion through facial movements, including changes in the position of the eyebrows, eyes, mouth, and other facial features that communicate a person's emotional or mental state. Facial affect is a primary channel of nonverbal social communication and can convey…

Facial Avatar(also: Singing head, Talking head avatar)

A digital, animated representation of a face — typically rendered as a 3D or stylized 2D character from the neck up — driven by audio, video, or data signals to produce expressive facial behavior such as lip-sync, emotional expression, gaze, and head motion. In accessibility…

Facial Expression

The use of facial muscles to convey emotions, reactions, or linguistic meaning. In sign languages such as ASL, facial expressions serve a grammatical function far beyond conveying emotion — they mark questions (raised eyebrows for yes/no questions, furrowed brows for…

Facial Expression Analysis(also: Automated Facial Expression Analysis, Facial Coding, AFEA)

The automated classification of a person's facial movements into discrete emotion categories (happy, angry, neutral, surprised, etc.) using computer vision. In hiring, facial expression analysis is embedded in AI-scored video interviews. It has been shown to systematically…

Facial Expression Recognition(also: FER, Facial Action Recognition)

Computer vision technology that detects and classifies facial expressions from images or video. In sign language contexts, facial expression recognition is essential for capturing non-manual signs — the facial movements that carry grammatical meaning in ASL, such as raised…

Facial Expressions in Sign Language(also: Non-Manual Markers, Non-Manual Signals, NMMs)

Meaningful facial movements and configurations that serve grammatical, lexical, and affective functions in sign languages. In American Sign Language, facial expressions are not merely emotional indicators but carry essential linguistic information including marking questions…

Facial Gesture Recognition(also: Face Tracking, Facial Expression Recognition)

Technology that uses cameras and computer vision algorithms to detect and interpret facial movements and expressions in real time. For accessibility, facial gestures such as opening the mouth, raising eyebrows, smiling, or nose movements can be mapped to computer commands,…

Facial Palsy(also: Bell's Palsy, Facial Paralysis, Unilateral Facial Palsy)

Facial palsy is a condition involving weakness or paralysis of the facial muscles, typically caused by damage to the facial nerve (cranial nerve VII). Bell's palsy is the most common form, appearing suddenly and usually affecting one side of the face. Facial palsy can…

Facial Recognition(also: Face Recognition, FR)

Facial recognition is a computer vision technology that identifies or verifies a person by analyzing and comparing patterns in their facial features from digital images or video. In accessibility contexts, facial recognition has significant potential to assist blind and low…

Facilitated Communication(also: FC, Supported Typing)

A technique in which a facilitator provides physical support to a person with a communication disability — typically by holding or steadying the person's hand, arm, or wrist — as they point to letters, words, or pictures on a communication board or keyboard. Originally promoted…

Failure Mode(also: Accessibility failure mode)

In accessibility evaluation, any hindrance caused by a product or web site that prevents a user with a disability from achieving a goal with the same effectiveness, efficiency or safety as a non-disabled user. The term is borrowed from reliability engineering and is used to…

Failure Point Barrier(also: Failure Point)

A type of access barrier where a task is completely impossible without assistive technology or support. Failure point barriers represent the most severe form of inaccessibility—without the necessary tool, there is no practical way to complete the task. Examples include a…

Failure Rate(also: FR (accessibility metric))

An accessibility metric introduced by Sullivan and Matson (2000) that, for a given page and a given checkpoint, divides the number of checkpoint violations found by the maximum number of violations that could have occurred on that page. Failure Rate produces a normalised value…

Fair Compensation(also: Equitable Compensation, Research Compensation)

The practice of providing adequate and equitable payment to research participants for their time, expertise, and contributions. In accessibility research, fair compensation is particularly important because participants with disabilities contribute specialized lived expertise…

Fall Detection(also: Automatic Fall Detection, Fall Alert System)

Technology that automatically identifies when a person has fallen and triggers an alert or emergency response. Fall detection systems typically use sensors such as accelerometers and gyroscopes in wearable devices (smartwatches, pendants), ambient sensors (radar, Wi-Fi), or…

Fall Prevention(also: Fall Risk Reduction, Falls Prevention)

Strategies, interventions, and technologies designed to reduce the risk of falls, particularly among older adults and people with mobility or balance impairments. Falls are a leading cause of injury, hospitalization, and loss of independence in aging populations. Fall prevention…

False Activation(also: Accidental Activation, Unintended Gesture)

An interaction error in gesture-based systems where the system incorrectly interprets a user's resting hand position or unintentional movement as a deliberate input command. In virtual reality, false activations are particularly problematic for users with motor impairments whose…

False Flagging(also: Malicious Flagging, Coordinated Flagging)

False flagging refers to the submission of content reports on social media platforms made in bad faith — that is, flagging posts that do not actually violate platform guidelines in order to suppress, harass, or remove legitimate content. It can be organized and coordinated, with…

False Negative(also: Type II Error)

An error in which a system fails to identify something that is actually present or true. In privacy and obfuscation contexts, a false negative occurs when an AI system fails to detect private content that should be obfuscated, potentially exposing sensitive information like…

False Positive(also: Type I Error)

An error in which a system incorrectly identifies something as present or true when it is not. In privacy and obfuscation contexts, a false positive occurs when an AI system incorrectly flags non-private content as private and applies obfuscation unnecessarily, potentially…

Family-Centered Learning(also: Family-Centered Education)

An educational approach that actively involves family members in the learning process, recognizing that home environments and family participation significantly impact learning outcomes, often more than school-based interventions alone. In the context of DHH children,…

Family-based Care(also: Family Caregiving Model, Home-based Care)

Family-based care is the model in which a relative — most often a parent, spouse, adult child, or sibling — is the primary caregiver for a disabled, chronically ill, or ageing family member, typically in the home rather than in an institutional setting. In the context of…

Farnsworth D-15 Test(also: D-15 Color Test, Farnsworth Dichotomous Test)

The Farnsworth D-15 test is a clinical assessment used to evaluate color perception by asking a person to arrange 15 colored caps in order of hue. The pattern of errors reveals the type and severity of color vision deficiency, distinguishing between protan (red), deutan (green),…

Fat Finger Problem(also: Fat Finger Effect, Finger Occlusion)

A fundamental challenge in touchscreen interaction where the user's finger is larger than the target being selected, causing difficulty in precise target acquisition. The finger both occludes (blocks the view of) the target during selection and creates ambiguity about the exact…

Fatigue(also: Disability-Related Fatigue, Physical Fatigue)

A common symptom across many disabilities and chronic conditions characterized by persistent exhaustion that is disproportionate to activity level and not fully relieved by rest. In technology and VR accessibility, fatigue has specific implications: users may have limited energy…

Feasibility Study(also: Feasibility Trial, Pilot Study)

A feasibility study is a small-scale investigation conducted before a full-scale trial to determine whether a planned intervention or system can be delivered as intended in its real-world setting. Feasibility work asks practical questions — Can we recruit? Can participants…

Feature Extraction(also: Feature Engineering, Representation Learning)

Feature extraction is the process of identifying and isolating measurable properties or characteristics (features) from raw data such as images, audio, or text, for use in machine learning tasks. In image processing, features may include edges, textures, colours, shapes, or…

Feature Hashing(also: Hashing Trick)

A technique used in machine learning to convert text or categorical data into fixed-length numerical feature vectors by applying a hash function. Feature hashing is particularly useful for handling high-dimensional sparse data, such as the text of bug reports or user reviews. It…

Federated Learning(also: FL)

A machine-learning approach in which a shared model is trained across many user devices without the raw training data ever leaving those devices: each device computes updates locally and sends only model parameters or gradients to a central server for aggregation. Federated…

Feedback Design(also: System Feedback, User Feedback Design)

The design of system responses that communicate to users what is happening, what the system understood, and what actions are needed. Effective feedback design is critical in assistive technology, where users may have limited sensory, motor, or cognitive channels for receiving…

Feedforward(also: Anticipatory Feedback)

Design information that tells users what to expect before they take an action, guiding them toward intended functionality by communicating expected results. Unlike feedback (which confirms what happened after an action), feedforward helps users form correct expectations and make…

Feminist HCI

An approach to human-computer interaction research and design articulated by Shaowen Bardzell that brings feminist theory, values, and methods into HCI practice. Feminist HCI foregrounds pluralism, embodiment, ecology, advocacy, self-disclosure, and participation; critiques…

Fetal Alcohol Spectrum Disorder(also: FASD, Fetal Alcohol Syndrome, FAS)

A group of conditions that can occur in a person whose mother consumed alcohol during pregnancy. Effects can include physical, behavioral, and learning problems, with a wide range of severity. FASD is relevant to digital accessibility because individuals may experience cognitive…

Few-Shot Learning(also: N-Shot Learning, Low-Shot Learning)

Few-shot learning is a machine learning approach that enables AI models to learn new concepts from only a small number of examples — typically 1 to 10 — rather than the hundreds or thousands traditionally required. This is achieved through techniques like meta-learning, where…