Situational impairments and sensing users

Intuition

Impairment is not only about permanent disability. Cold hands, a noisy tram, stress or a heavy bag all make the same phone harder to use. Designing for those moments is accessibility too.

Situational impairments are caused by the moment, not the person

Part 2 of Lecture 10 is the lecturer’s research overview, titled “Towards Accessible, Context-Aware and Emotionally Intelligent Devices”, with the aim of creating accessible smart solutions that understand and respond to us. It splits into Accessibility and Instrumentation.

Situationally-induced impairments and disabilities (Sears and Young, 2003) are covered through effects of cold ambient temperature (UbiComp 2016), ambient noise (IMWUT 2018), stress (IMWUT 2019) and ambient light (INTERACT 2019). The noise study is the one from Lecture 8.

Encumbrance and walking change mixed reality interaction

A CHI 2025 study (Li, Velloso, Withana, Sarsenbayeva) looked at mixed reality, since its ubiquitous nature might change how we perform daily activities. Conditions: encumbrance of 0 kg, 0.5 kg or 1.0 kg, and motion, standing or walking. Tasks: target acquisition by direct selection, target acquisition by ray-casting, and text entry. Heavier load and walking made performance worse across movement time, offset, error rate and throughput, with 1.0 kg while walking worst. The slide percentages extracted unreliably, so check the slide for exact numbers. Implications: everyday environmental constraints matter, and research should leave confined lab spaces.

WICE (Weight-Induced Consumed Endurance, UIST 2025) is a model to quantify shoulder fatigue with weighted objects. It relates workload, effort, physiological strain and endurance to fatigue and recovery. The model equations on the slides did not extract. WICE is a foundation for sensing and adapting to encumbrance, for example using a built-in camera to detect a held object and estimate its weight.

Instrumentation senses and induces states in users

Sensing: cold-induced situational impairments sensed from smartphone battery temperature (UbiComp 2017), and emotions, asking whether smartphone use drives emotions or the reverse (CHI 2020, the field study in Lecture 8).

Inducing emotions: an immersive and interactive VR dataset to elicit emotions (ISMAR 2024). Traditional methods use music, movies, images and 360 degree videos. The study had 160 participants on Prolific, 80 per condition (VR or 360 degree videos), with self-reports after each scene (SAM). Targeted emotions were subjectively elicited, and a “shouting man with gun” scene stood out with emotional bleeding or residue. The contribution was testing and validating emotion induction in VR and the first dataset of its kind.

Inducing empathy: a voice assistant study (IMWUT/UbiComp 2025). Conditions were perceived age of a female voice (Nova, an older female, perceived 65+; Nexa, Alexa’s standard female voice) and response style (humorous, apologetic, none). Variables: empathy, trust and service recovery satisfaction, across tasks from shopping cart, entertainment, timers and reminders, Q&A, news and weather, and home environment. Findings: the older voice had positive effects, apologetic and humorous responses helped empathy, no acknowledgement hurt trust and satisfaction, and effects were stronger in male participants. The contribution: perceived old age and humorous or apologetic responses support empathy and better failure recovery.

Optional aside

Examinability of this part is uncertain. It is the second half of Lecture 10 and the brief for this site treats Lecture 10 as examinable, but the content is the lecturer’s own research rather than a framework. Prioritise colour and contrast first. The same voice assistant study is covered from the student researcher’s side in the guest lecture (non-examinable).

Pitfall

Do not memorise the percentages. The slides extracted them unreliably, and the point to hold is the direction: more load and walking means worse performance.

Recall

Which four situational factors does the lecture name?

Cold ambient temperature, ambient noise, stress and ambient light.