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Smartstep – balance and brain training


We are seeking volunteers aged 65+ to participate in our smartstep research study.

Registration now closed. 
If you have any questions, please contact the smartstep team by telephone: (02) 9399 1255 or email: smartstep@neura.edu.au

This study aims to investigate the benefits of balance training and brain training on physical functions (balance and mobility), cognitive functions, general health and accidental fall events in people aged 65+ years.

The smartstep training system has been designed to enable you to undertake training in your own home, by playing engaging and enjoyable computer games. The system connects to a TV or computer monitor. The games are played with either a step mat (Figure 1) or a touch pad (Figure 2). These games have been designed to train important balance and cognitive functions, while also being fun. You may recognise some of the games, such as Space Invaders and Tetris (Figure 3).

To participate, you must be:

• 65 years of age or older
• English-speaking
• Living in the Sydney metropolitan area
• Able to perform everyday activities independently (eg.walk household distances)
• Have no neurodegenerative condition such as Parkinson’s disease, Multiple Sclerosis, Dementia or Alzheimer’s disease.
• Agreeable to participate for 1 year.

Smartstep Touch Pad (Figure 1)                            Smartstep Step Pad (Figure 2)

This study will involve an initial appointment at NeuRA to assess your fall risk, using measures of strength, balance, vision, reaction time, stepping, walking and cognitive function. You will be asked some questions about your general health, physical activities, medication use and falls history.

After the baseline assessments, you will be randomly assigned to one of three groups:
1. The step training group: You will receive a step mat and game system and be asked to play for 120 minutes/week for 1 year.
2. The seated training group: You will receive a touch pad and game system and be asked to play for 120 minutes/week for 1 year.
3. The control group: you will receive information regarding health and fall prevention.

Smartstep Computer Games

Space Invaders and Tetris computer games (Figure 3)

See what’s going on at NeuRA


What is the analgesic effect of EEG neurofeedback for people with chronic pain? A systematic review

Researchers: A/Prof Sylvia Gustin, Dr Negin Hesam-Shariati, Dr Wei-Ju Chang, A/Prof James McAuley, Dr Andrew Booth, A/Prof Toby Newton-John, Prof Chin-Teng Lin, A/Prof Zina Trost Chronic pain is a global health problem, affecting around one in five individuals in the general population. The understanding of the key role of functional brain alterations in the generation of chronic pain has led researchers to focus on pain treatments that target brain activity. Electroencephalographic (EEG) neurofeedback attempts to modulate the power of maladaptive EEG frequency powers to decrease chronic pain. Although several studies provide promising evidence, the effect of EEG neurofeedback on chronic pain is uncertain. This systematic review aims to synthesise the evidence from randomised controlled trials (RCTs) to evaluate the analgesic effect of EEG neurofeedback. The search strategy will be performed on five electronic databases (Cochrane Central, MEDLINE, Embase, PsycInfo, and CINAHL) for published studies and on clinical trial registries for completed unpublished studies. We will include studies that used EEG neurofeedback as an intervention for people with chronic pain. Risk of bias tools will be used to assess methodological quality of the included studies. RCTs will be included if they have compared EEG neurofeedback with any other intervention or placebo control. The data from RCTs will be aggregated to perform a meta-analysis for quantitative synthesis. In addition, non-randomised studies will be included for a narrative synthesis. The data from non-randomised studies will be extracted and summarised in a descriptive table. The primary outcome measure is pain intensity assessed by self-report scales. Secondary outcome measures include depressive symptoms, anxiety symptoms, and sleep quality measured by self-reported questionnaires. Further, we will investigate the non-randomised studies for additional outcomes addressing safety, feasibility, and resting-state EEG analysis.