Synopsis

Brain–computer interfaces (BCIs) are emerging as tools that complement conventional neurorehabilitation approaches. This presentation demonstrates how motor-imagery-based BCI systems measure and respond to neural activity associated with attempted movement, even when visible movement is limited.

Through real-time EEG signal visualisation and virtual avatar movement, participants will observe how a typical neurorehabilitation session runs. The session will illustrate how therapists can use this closed-loop system to promote neuroplasticity and reinforce motor imagery during upper-limb rehabilitation.

Practical considerations for integrating neurotechnology into rehabilitation workflows will be discussed, helping clinicians understand where BCI-assisted therapy may complement existing occupational therapy and interdisciplinary rehabilitation approaches.

Aim(s) of Presentation
1. Introduce the neurophysiological principles underlying motor-imagery BCIs used in neurorehabilitation.
2. Demonstrate how EEG signals and imagined movement are used to promote neuroplastic recovery of the upper limbs.
3. Provide clinicians with practical insight into how neurofeedback-driven training are incorporated into rehabilitation workflows.


Target Audience

Allied health professionals working with clients with stroke, MS, or Parkinson's disease.

Key Outcomes

Participants will:
• Learn how motor imagery produces measurable EEG patterns associated with attempted movement.
• Observe how real-time feedback reinforces motor imagery training.
• Gain insight into how BCI-assisted rehabilitation approaches may complement existing therapy strategies.


Potential Value for the Profession

Neurotechnologies offer new ways to observe and reinforce controlled neuroplasticity. By introducing clinicians to how BCIs measure and respond to motor imagery, this session aims to broaden awareness of how such technologies may complement conventional rehabilitation practices and support innovation within occupational therapy/interdisciplinary neurorehabilitation.

Synopsis
Occupational therapists may make clinically sound home modification recommendations, yet intended outcomes can still be weakened during delivery. This presentation explores four common barriers between prescription and implementation: unclear scope, site and structural constraints, budget and timing pressures, and difficulty translating measurements into buildable, compliant specifications. Using practical examples from everyday home modification practice, the session will show how these barriers can affect safety, compliance, communication, and client outcomes.

Aims of presentation
To examine common implementation barriers in home modifications and share practical approaches that help recommendations remain achievable, compliant, and aligned with the original clinical intent.

Target audience
Occupational therapists involved in home modifications, assistive technology, discharge planning, rehabilitation, ageing in place, and community-based practice.

Key outcomes
Participants will be able to identify four common barriers to home modification delivery, recognise how these barriers influence safety, compliance, and project outcomes, and apply practical strategies to improve scope clarity, feasibility, and implementation.

Potential value for the profession
This presentation supports occupational therapists to strengthen the link between assessment and delivery. By focusing on practical implementation challenges, it encourages clearer communication, more feasible specifications, and safer, more timely home modification outcomes.

Synopsis
Early career therapists often describe their transition to practice as steep, overwhelming, and emotionally demanding, which can quickly impact confidence and wellbeing, contributing to burnout and early resignation. In parallel, many clinical supervisors step into supervision roles with limited formal training, relying on their own experiences rather than evidenced-based models.
This presentation introduces a structured supervision approach grounded in the Conscious Competence Model. A clear visual representation of competence development anchors reflective discussions in observable stages of growth, transforming abstract conversations into structured, goal-oriented learning.
For supervisees, the framework normalises the early-career learning curve, by externalising uncertainty as a predictable developmental stage rather than personal inadequacy.
For supervisors, the model provides a tangible, strengths-based structure that promotes dialogue and reflection— particularly valuable for supervisors building their own confidence.
Implementation demonstrates shared benefits for supervisors and supervisees, including increased confidence, stronger professional identity formation, enhanced role satisfaction, and capability development. Supervisees additionally report improved wellbeing and deeper engagement in supervision, while organisations note improved retention.
Aims of Presentation
-Present a structured developmental supervision model benefiting supervisees and supervisors.
-Provide practical, growth- and outcome-focused supervision tools
Target Audience
-Clinical supervisors and managers
-Early career therapists
-Organisations seeking to strengthen supervision quality
Key Outcomes
-Appling a developmental framework for strengths-based, high-quality supervision
-Normalising the early-career learning curve to reduce burnout risk and resignation.
-Strengthening supervisors/supervisees’ confidence and capability
Potential Value for the Profession
Embedding developmental theory into supervision strengthens capability, supports wellbeing and professional growth, and improves workforce sustainability across the profession.

Artificial intelligence (AI) has the potential to dramatically improve how Occupational Therapists deliver their services. From automated summaries to predictive insights to support decision-making, AI tools offer efficiency; but also introduce new ethical, privacy, and professional challenges. Implementing AI responsibly requires a clear understanding of ethical frameworks, data governance, and accountability within the Australian healthcare context.
This session translates the key ethical principles of transparency, fairness, and accountability into practical steps for small to medium OT businesses wanting to implement AI. Drawing on examples of tools currently being adopted across OT and other healthcare sectors, the session explores how to evaluate AI tools, establish consent and information-handling protocols, and apply Australian privacy legislation in digital workflows.
Using real-world examples, this session will demonstrate how clinicians can identify and mitigate common ethical risks, such as bias, inappropriate data use, or over-reliance on automation. Participants will gain access to practical resources, including an AI implementation checklist and vendor evaluation guide, to support safe and compliant technology adoption.
By moving beyond theory to action, this session will empower Occupational Therapists and practice owners to engage confidently with AI. Attendees will leave with the knowledge and tools to implement AI ethically; ensuring AI technology is used to enhance their clinical reasoning and professional values.