Background insights

Over the last decade, interest in neurotechnology, brain-computer and brain-machine interface (BCI and BMI) technologies has heightened. BCI depends on the interaction of the user’s brain and the system itself (either directly or through a bi-directional link between the brain and a computer or external device). An algorithm translates this neural activity into specific commands.

The BNCI (Brain/Neural Computer Interaction) Horizon 2020 project of the European Commission for coordinating BCI research refers to a number of major applications Those that are directly relevant to this Challenge are: to improve functionality (e.g. rehabilitate upper or lower limbs after a stroke), to replace human functions (e.g. BCI controlled neural prostheses) or to restore other human functions (e.g. unlocking those who have ‘locked in’ syndrome or are unable to communicate).

For people who cannot communicate, there have been some especially exciting device discoveries including the Australian-invented Stentrode described as “a paper clip sized device that allows a computer to read a patient’s thoughts” giving new hope to those living with motor neurone disease, muscular dystrophy and spinal cord injuries.

BCI can be invasive or non-invasive but where the aim is to restore mobility, invasive procedures have been favoured so far. Stimulating muscle by BCI-driven functional electrical stimulation while bypassing the central nervous system is a typical approach. Non-invasive methods have traditionally had less reliable signals and less precise outcomes. However, 2019 saw the invention of the first-ever successful mind-controlled robotic arm to continuously track and follow a computer cursor. Bin He at Carnegie Melton University says this breakthrough using non-invasive signals could actually bring safe and affordable BCI to people needing assistive devices much like smartphones

This has brought the ‘holy grail’ of less invasive or totally non-invasive neurotechnology to give paralysed patients control over their environment a lot closer. That said, the success of BCI is impacted by many different neuro-psychological factors e.g. underlying emotion and empathy, attention span, memory load and fatigue plus physiological factors that are constantly changing. Dealing with those factors and designing sensors with better signal resolution are vital but the technology options are also fast changing.

Alongside BCI, artificial intelligence, natural speech generation, wireless body area networks and machine learning are helping to accelerate new classes of BCI-enabled communication and movement devices. Wearable BCIs are already on the horizon to change the lives of those living with complex disabilities. However, the impact of artificial intelligence on bionic solutions goes beyond restoring or enabling communication and bionic mobility.

AI-enabled organs and organ software is a new frontier. Queensland-based Neuromathix’ artificial pancreas software adopts a completely new form of AI. Dr Nigel Greenwood’s two competing AIs (an adversarial system in the one software) provides the insights needed to internally develop and deliver a customised insulin strategy for people living with ‘rollercoaster’ of brittle Type 1 diabetes. The likelihood that Diabetes Neuromathix’ software will save the lives of millions and bring their health costs down will no doubt stimulate interest in new AI-enabled organ innovations.

Deep brain stimulation (DBS) for Parkinson’s disease with the aim of dramatically reducing tremors, rigidity and gait problems is also advancing with the assistance of artificial intelligence. Apart from an implanted neurostimulator (that uses a pulse generator to deliver electrical current to the DBS target), deep brain electrodes can be bi-directionally connected to monitor electrical activity and progressively identify warning signals of tremors. An AI-driven stimulator is then able to generate signals occasionally rather than continuously to control the tremors. These recent advances in DBS are expected to inform new treatments for obsessive-compulsive disorder (OCD), Gilles de la Tourette syndrome and depression. Bi-directional electrodes which stimulate and record from deep brain structures (a closed-loop DBS) have many uses (Warwick, 2018; Brain and Neuroscience Advances, V2).

Taking BCI and even DBS treatments to a wider market is challenging, requiring new standards and more non-invasive, but highly reliable devices and wearables. Consumer-centred R&D has been limited to small pockets of individuals with complex disabilities. However, design thinking innovation models involving a wider suite of end users are desirable (and likely) as advances in neurotechnology and AI bring ‘nextgen’, non-invasive BCI and allied wearables.

Winners of the Neural and AI-enabled Bionics Challenge will deliver a ‘new to the world’ innovation or notable advance in neurotechnology or AI-enabled bionics. Key areas of interest are:

Brain-computer interfaces (BCI) or brain-device interfaces, AI-enabled implanted devices or wearables that enable communication (interaction between thought, message formulation, speech and/or other communication)

BCI, deep brain stimulation, AI-enabled devices and wearables that contribute to improved treatments and functionality for people living with emotional or nervous disorders, epilepsy, disabilities caused by stroke or spinal cord injury, chronic peripheral neuropathies and neurodegenerative diseases (e.g. Parkinson’s disease, MND, cerebral palsy)

BCI, AI-enabled software and allied devices and wearables that restore or replace the functionality of human organs, senses and limbs

Allied technologies, health services or program innovations that heighten consumer adaption to neurobionics treatments, BCI and AI-enabled devices

Bionics Queensland Challenge 2020 – Be in it to win it!