35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13)

July 4, 2013

Evaluation of a Smartphone-based audio-biofeedback system for improving balance in older adults – A pilot study

ThB23.10

Anthony Fleury1, Quentin Mourcou1,2, Céline Franco2,3,4, Bruno Diot2,3, Jacques Demongeot2, Nicolas Vuillerme2,5 (1) Mines Douai, Computer Sciences and Automation Dpt. Mines Telecom Institute (2) Univ. Grenoble-Alpes, FRE 3405 AGIM Laboratory, CNRS-UJF-UPMF-EPHE, 38706 La Tronche (3) IDS, 2 av. des puits, 71300 Montceau-les-Mines, France (4) UJF-Grenoble1/CNRS/TIMC-IMAG UMR5525, 38041 Grenoble (5) Institut Universitaire de France, France

Contact : [email protected] Introduction and iBalance system presentation

Material and Method

Objectives: (1) proposing a mobile quantified-self application embedded in a smartphone for measurement, training and correction of balance and (2) testing its usability by elderly people.

Dead Zone

ABF on Left Ear

ABF on Right Ear

Audio-Biofeedback (ABF) trigger

 The user wears an iPhone containing the application.  This one includes series of exercises that can be done by the user independently, whenever and wherever he wants.

• A simple User Interface allows to run a set of experiments read out by Text To Speech and displays reports. • The whole acquisition system is based on the sensors embedded in the smartphone. A Kalman filter estimates the angles of inclination in both Anterior-Posterior (AP) and Medial-lateral (ML) directions. • When ML angle is out of a predefined ”dead zone”, the corresponding ear is stimulated by a sound (Red Zones vs. Green Zone) • Protocol: Three 30-s trials for each randomized Parallel vs Tandem Stance experimental condition (1) Parallel / No-ABF (Audio-BioFeedback), (2) Parallel / ABF, (3) Tandem / No-ABF (4) Tandem / ABF • Population: Six healthy elderly (age: 62.7 ± 2.7 kg; height: 173.0 ± 9.1 cm; weight: 86.2 ±9.1 kg, mean ± SD)

 An audio biofeedback mode is available for training or correction sessions.  The remote monitoring loop allows sending reports of the sessions to the medical staff.

Results ABF

No-ABF

120

0,12

100

**

80 60 40 20

Percentage of time in the green zone (vs red zones) whether there is biofeedback (ABF) or not (No-ABF).

0

ABF

Tandem Stances

2,00

*

0,08 0,06

Mean Power Frequency (MPF) of the ML signal.

NS

0,04 0,02

ABF

*

1,75

0,10

1,50

Root mean square (RMS) of the ML angle.

1,25 1,00 0,75 0,50

NS

0,25

0,00

Parallel

No-ABF

ML Trunk tilt RMS (°)

NS

ML Trunk tilt MPF (Hz)

Percentage of time within the DZ (%)

No-ABF

0,00

Parallel

Tandem Stances

Parallel

Tandem Stances

• Effect of the stance on the three variables:  Time inside the dead-zone decreases for tandem as the difficulty of the position increases the quantity of movement.  MPF increases due also to this instability.  RMS values also highlight the adversity of the feet position. • However, we can note that the ABF condition ALWAYS significantly improves the execution of the tandem stance  This means that this very simple ABF system has been correctly used by these elderly persons (without a huge training). • No significantly statistical effect on AP has been noticed.

Conclusion and discussion

• After measuring the effect of audio biofeedback on young people [1], this study performed on older adults showed that the audio-biofeedback system implemented on smartphone is both well-accepted and well-used by the elderly as it significantly decreases the effect of an adverse feet position (tandem) during 30-s trials. • Our easy-to-use iBalance system allows an automatically driven experimental session, with a report at the end for medical care  perfect for home medication in order to improve balance in older adults following a prescription that could be given as a protocol. • iBalance is autonomous and uses the huge computation and measurement abilities of our smartphones, devices that are now well spread and user friendly in addition to be “affordable” (comparing to lab material). [1] C. Franco, A. Fleury, P.Y. Gumery, B. Diot, J. Demongeot, and N. Vuillerme, “iBalance-ABF: A Smartphone-Based Audio-Biofeedback Balance System,” IEEE Trans Biomed Eng, vol. 60(1), pp. 211-5, 2013.