Mobile App Rehabilitation for Speech Disorders

Overseen By Yunjung Kim

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Florida State University

Disqualifiers: Severe speech impairment, Neurological disorders, Severe mental disorders, Illiteracy, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 10

36 Participants Needed

Trial Summary

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It is best to discuss this with the trial coordinators or your doctor.

What data supports the effectiveness of the treatment Smart-phone based, self-driven speech rehabilitation?

Research shows that mobile apps can effectively support speech therapy. For example, a study found that an iPad app using automatic speech recognition helped improve speech accuracy in people with speech disorders, and users enjoyed the app. This suggests that smartphone-based speech rehabilitation could also be effective and engaging. ^{1 2 3 4 5}

Is mobile app rehabilitation for speech disorders safe for humans?

Research on mobile app-based speech therapy, like the SayBananas! game and ReaDySpeech program, shows that these tools are generally safe for users, including children and adults with conditions like Parkinson's disease and post-stroke speech issues. Participants in these studies reported positive experiences and improvements in speech, suggesting that these apps are a safe option for speech rehabilitation. ^{1 2 6 7 8}

How is the mobile app rehabilitation for speech disorders treatment different from other treatments?

This treatment is unique because it uses a smartphone app to allow patients to independently practice speech exercises at home, providing feedback through automatic speech recognition (ASR) technology. This approach empowers patients to manage their own therapy and maintain improvements outside of traditional face-to-face sessions, which is different from standard treatments that typically require in-person therapy with a clinician. ^{2 3 9 10 11}

What is the purpose of this trial?

This study evaluates the efficacy of smartphone-based speech therapy administered at home compared with usual care. Participants will be randomized into the treatment and waitlist control groups with an allocation ratio of 1:1.

Research Team

Jinwoo Kim, PhD

Principal Investigator

Haii Corp.

Eligibility Criteria

This trial is for individuals who have speech difficulties due to conditions like dysarthria or stroke. Participants should be able to use a smartphone and commit to self-driven speech therapy at home.

Inclusion Criteria

Patients must be able to use a smartphone-based speech therapy application, as determined by self-reporting cognitive abilities

Speaks English as a native language

Exclusion Criteria

Unable to use smartphone application or conduct speech assessment due to severe speech impairment

Illiterate patients

I have a progressive neurological disorder that affects my speech.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment Phase 1

Participants receive smartphone-based speech therapy for 4 weeks

4 weeks

5 sessions per week (home-based)

Treatment Phase 2

Participants continue with the crossover design, receiving the alternative intervention for 4 weeks

4 weeks

5 sessions per week (home-based)

Follow-up

Participants are monitored for safety and effectiveness after treatment

8 weeks

Treatment Details

Interventions

• Smart-phone based, self-driven speech rehabilitation

Trial Overview The study tests if using a smartphone app for speech rehabilitation at home is as effective as the standard care people usually receive. Participants are randomly placed into either the treatment group or put on a waitlist (control group).

Participant Groups

Group I: Intervention Experimental Treatment 1 Intervention

Participants in the intervention group will use a speech therapy application, a software designed for post-stroke dysarthria speech therapy and provided in the form of a mobile application. The application provides intensive speech treatment, including respiration, phonation, resonance, prosody, and articulation exercises. The system analyzes patients' voices collected while using the application and delivers the results through real-time visual and summary feedback, increasing patients' ability to self-monitor.

Group II: Waitlist control Active Control 1 Intervention

Who Is Running the Clinical Trial?

Florida State University

Lead Sponsor

Trials

234

Recruited

41,100+

Findings from Research

The iPad-based speech therapy app using automatic speech recognition (ASR) showed an 80% agreement with human judgment on speech accuracy, indicating reliable feedback for users.

Participants with apraxia of speech and aphasia demonstrated significant improvements in word production accuracy over a 4-week therapy program, with gains maintained one month after treatment, suggesting the app's effectiveness as a therapeutic tool.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Feasibility of Automatic Speech Recognition for Providing Feedback During Tablet-Based Treatment for Apraxia of Speech Plus Aphasia. Ballard, KJ., Etter, NM., Shen, S., et al.[2020]

The E-learning-based speech therapy (EST) application allows patients with dysarthria to engage in intensive speech training at home, complementing traditional face-to-face therapy and enabling independent maintenance of speech quality after therapy ends.

Therapists can remotely create personalized training programs and monitor patient progress, while the EST system also collects valuable data on dysarthric speech for future research.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

E-learning-based speech therapy: a web application for speech training. Beijer, LJ., Rietveld, TC., van Beers, MM., et al.[2010]

A wearable biofeedback device was developed to help patients with Parkinsonism improve their speech intensity outside of clinical settings, addressing a common challenge in speech therapy.

The study showed that patients were able to transfer significant improvements in their speech from the clinic to everyday situations while using the device, indicating its potential effectiveness for ongoing treatment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A microcomputer-based wearable biofeedback device to improve transfer of treatment in parkinsonian dysarthria. Rubow, R., Swift, E.[2019]

The Q-Voz application, designed for voice therapy, received positive feedback from seven speech therapists, who found it useful for helping patients with dysphonia improve their voice-related habits.

All evaluators agreed that the app could facilitate easier changes in voice behavior for patients, suggesting it can be an effective auxiliary tool in voice rehabilitation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Prototype app for voice therapy: a peer review. Lavaissiéri, P., Melo, PE.[2022]

References

1. England pubmed.ncbi.nlm.nih.gov

Equitable access to speech practice for rural Australian children using the SayBananas! mobile game. [2023]

2. United States pubmed.ncbi.nlm.nih.gov

Feasibility of Automatic Speech Recognition for Providing Feedback During Tablet-Based Treatment for Apraxia of Speech Plus Aphasia. [2020]

3. United States pubmed.ncbi.nlm.nih.gov

Mobile apps for treatment of speech disorders in children: An evidence-based analysis of quality and efficacy. [2019]

4. United States pubmed.ncbi.nlm.nih.gov

Integrating the iPad into an intensive, comprehensive aphasia program. [2014]

5. United States pubmed.ncbi.nlm.nih.gov

An iOS-based Cepstral Peak Prominence Application: Feasibility for Patient Practice of Resonant Voice. [2022]

6. United States pubmed.ncbi.nlm.nih.gov

Treating Speech Movement Hypokinesia in Parkinson's Disease: Does Movement Size Matter? [2023]

7. England pubmed.ncbi.nlm.nih.gov

A feasibility randomized controlled trial of ReaDySpeech for people with dysarthria after stroke. [2022]

8. France pubmed.ncbi.nlm.nih.gov

[Rehabilitation strategies of dysfunctional dysphonias in relation to posture]. [2015]

9. United States pubmed.ncbi.nlm.nih.gov

E-learning-based speech therapy: a web application for speech training. [2010]

10. United States pubmed.ncbi.nlm.nih.gov

A microcomputer-based wearable biofeedback device to improve transfer of treatment in parkinsonian dysarthria. [2019]

11. Brazil pubmed.ncbi.nlm.nih.gov

Prototype app for voice therapy: a peer review. [2022]