Sonification for Personalised Gait Intervention

Abstract

Mobility challenges threaten physical independence and good quality of life. Often, mobility can be improved through gait rehabilitation and specifically the use of cueing through prescribed auditory, visual, and/or tactile cues. Each has shown use to rectify abnormal gait patterns, improving mobility. Yet, a limitation remains, i.e., long-term engagement with cueing modalities. A paradigm shift towards personalised cueing approaches, considering an individual's unique physiological condition, may bring a contemporary approach to ensure longitudinal and continuous engagement. Sonification could be a useful auditory cueing technique when integrated within personalised approaches to gait rehabilitation systems. Previously, sonification demonstrated encouraging results, notably in reducing freezing-of-gait, mitigating spatial variability, and bolstering gait consistency in people with Parkinson's disease (PD). Specifically, sonification through the manipulation of acoustic features paired with the application of advanced audio processing techniques (e.g., time-stretching) enable auditory cueing interventions to be tailored and enhanced. These methods used in conjunction optimize gait characteristics and subsequently improve mobility, enhancing the effectiveness of the intervention. The aim of this narrative review is to further understand and unlock the potential of sonification as a pivotal tool in auditory cueing for gait rehabilitation, while highlighting that continued clinical research is needed to ensure comfort and desirability of use.

Keywords: Parkinson’s disease; gait; personalised rehabilitation; sonification; wearables.

Figure 1

This graph displays the waveforms of musical notes A1 and A5 sampled at a rate of 44.1 kHz. The waveform of the A1 note has a lower frequency of 110 Hz, while the green curve represents the A5 note with a higher frequency of 880 Hz, demonstrating that the ‘closer’ the waves, the higher the pitch.

Figure 2

The graph displays three sine waves, each generated at 440 Hz but with different amplitudes of 10 dB, 30 dB, and 50 dB, demonstrating that a higher waveform results in a higher amplitude.

Figure 3

Displays waveforms of 3 audio signals: human voice, piano, and tuning fork, all centred around 440 Hz fundamental frequency. Timbre varies in all due to the difference in unique harmonic structure, seen in each waveform.

Figure 4

A diagram outlining the steps commonly taken during the phase vocoder algorithm for pitch shifting and time-stretching purposes.

Figure 5

A diagram illustrating the DRC algorithm and how it is used to increase and decrease gain on audio input based on a set threshold.

Figure 6

This diagram provides examples, referred to in text, of how sonification and auditory manipulation techniques could be applied to gait rehabilitation, illustrating the extraction of various features from inertial measurement units (IMUs) on the feet. The IMU-based gait characteristics could undergo sonification to generate biofeedback acoustic variables through specialized auditory techniques, thereby changing the person’s gait.

Figure 7

This box plot illustrates the distribution of mean/initial steps per minute (SPM) ratios for two conditions: verbal instruction and noise feedback—fixed target. The blue lines indicate the SPM ratio (1) and the target SPM ratio (1.5).

Figure 8

Eta Squared (η2G%) values for the top five outcome measures. The bar chart represents the η2G% for the New Freezing of Gait Questionnaire (NFOGQ), Parkinson’s Disease Questionnaire-39 mobility domain (PDQ39 mobility), Unified Parkinson’s Disease Rating Scale Part III (UPDRSIII), PDQ39 bodily discomfort, and PDQ39 total. Notably, NFOGQ exhibits the highest η2G% value.

Figure 9

A bar chart illustrating the results of the experiment, demonstrating the significant effectiveness of sonification in increasing step length.