Early detection and tracking of bulbar changes in ALS via frequent and remote speech analysis

Stegmann, Gabriela; Hahn, Shira; Liss, Julie; Shefner, Jeremy M.; Rutkove, Seward B.; Shelton, Kerisa; Duncan, Cayla Jessica; Berisha, Visar

doi:10.1038/s41746-020-00335-x

Cited by 47 publications

(34 citation statements)

References 21 publications

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“…Stegmann et al evaluated the repeatability of acoustic and language features of collected longitudinal speech from three separate samples (healthy controls, ALS patients, ALS patients with suspected frontotemporal dementia) [ 16 ]. The acoustic and language features were extracted using open source, including openSMILE, Talk2me, and Praat.…”

Section: Resultsmentioning

confidence: 99%

Digital Biomarkers for Neuromuscular Disorders: A Systematic Scoping Review

Youn

Moon

et al. 2021

Diagnostics

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Biomarkers play a vital role in clinical care. They enable early diagnosis and treatment by identifying a patient’s condition and disease course and act as an outcome measure that accurately evaluates the efficacy of a new treatment or drug. Due to the rapid development of digital technologies, digital biomarkers are expected to grow tremendously. In the era of change, this scoping review was conducted to see which digital biomarkers are progressing in neuromuscular disorders, a diverse and broad-range disease group among the neurological diseases, to discover available evidence for their feasibility and reliability. Thus, a total of 10 studies were examined: 9 observational studies and 1 animal study. Of the observational studies, studies were conducted with amyotrophic lateral sclerosis (ALS), Duchenne muscular dystrophy (DMD), and spinal muscular atrophy (SMA) patients. Non-peer reviewed poster presentations were not considered, as the articles may lead to erroneous results. The only animal study included in the present review investigated the mice model of ALS for detecting rest disturbances using a non-invasive digital biomarker.

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Section: Resultsmentioning

confidence: 99%

Digital Biomarkers for Neuromuscular Disorders: A Systematic Scoping Review

Youn

Moon

et al. 2021

Diagnostics

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“…This observation is complemented by the results presented in this SLR, which also reports the limited number of neuroimaging-based studies aimed at diagnosis support applications and survival prediction of the ALS disease, despite the potential mentioned by van der Burgh et al [ 56 ]. In addition to these biomedical signs mentioned so far, studies show the feasibility of using the speech biosignal for the early diagnosis of ALS, as indicated by Wang et al [ 76 ], Suhas et al [ 77 ], An et al [ 78 ], Vieira et al [ 79 ], and Wisler et al [ 80 ], and tracking changes in individuals with bulbar ALS [ 81 ].…”

Section: Discussionmentioning

confidence: 99%

Biomedical signals and machine learning in amyotrophic lateral sclerosis: a systematic review

et al. 2021

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Introduction The use of machine learning (ML) techniques in healthcare encompasses an emerging concept that envisages vast contributions to the tackling of rare diseases. In this scenario, amyotrophic lateral sclerosis (ALS) involves complexities that are yet not demystified. In ALS, the biomedical signals present themselves as potential biomarkers that, when used in tandem with smart algorithms, can be useful to applications within the context of the disease. Methods This Systematic Literature Review (SLR) consists of searching for and investigating primary studies that use ML techniques and biomedical signals related to ALS. Following the definition and execution of the SLR protocol, 18 articles met the inclusion, exclusion, and quality assessment criteria, and answered the SLR research questions. Discussions Based on the results, we identified three classes of ML applications combined with biomedical signals in the context of ALS: diagnosis (72.22%), communication (22.22%), and survival prediction (5.56%). Conclusions Distinct algorithmic models and biomedical signals have been reported and present promising approaches, regardless of their classes. In summary, this SLR provides an overview of the primary studies analyzed as well as directions for the construction and evolution of technology-based research within the scope of ALS.

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“…Identifying and addressing problematic symptoms can minimize their effects on a person's function, health, and quality of life. This management can be enhanced by healthcare professionals using telehealth technologies in patient care and training and support of carers (Andrews et al, 2020; Helleman et al, 2020; Stegmann et al, 2020) throughout disease progression. These telehealth technologies can include multidisciplinary rehabilitation programs, nutrition, ventilation and pharmacology, brain–computer interfaces and eye-tracking, augmentative communication and environment control, virtual-reality, and mobile/computer applications that can connect patients to their multidisciplinary teams daily, providing alternative dynamic connecting tools.…”

Section: Discussionmentioning

confidence: 99%

Effects of prolonged interruption of rehabilitation routines in amyotrophic lateral sclerosis patients

Gonçalves

Magalhães

2021

Pall Supp Care

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Objective Patients with amyotrophic lateral sclerosis (ALS) experienced prolonged interruption of their rehabilitation palliative care routines due to restrictive COVID-19 pandemic public health measures. This study assesses the effects of before and after the lockdown on functionality rates and quality of life (QoL) in patients with ALS. Methods A longitudinal observational study was conducted. Participants were assessed three times — early January (T0), before mandatory lockdown (T1), and during lockdown (T2) — using the ALS Functional Rating Scale-revised (ALSFRS-R), Fatigue Severity Scale (FSS), and the ALS-Specific Quality of Life-Short Form (ALSSQOL-SF). The paired-sample t-test and Wilcoxon signed-rank test were used. Results Thirty-two patients were included with a mean age of 56.9 (SD 14.2) years and mean symptoms onset of 27.1 (SD 14.3) months. ALSFRS-R mean scores decayed significantly over time when comparing T0–T1 (0.26 ± 0.38) and T1–T2 (1.36 ± 1.43) slopes (p < 0.001). Significant differences were observed between T1 and T2 for ALSSQOL-SF scores (115.31 ± 17.06 vs. 104.31 ± 20.65), especially in four specific domains, and FSS scores (34.06 ± 16.84 vs. 40.09 ± 17.63). Negative correlations between negative emotions and physical symptoms assessed by ALSSQOL-SF and FSS were found. Significance of the results Rehabilitation treatment routines in palliative care, such as physiotherapy and speech therapy, appear to mitigate the ALSFRS-R slope. Prolonged interruption of rehabilitation during the lockdown may have accelerated the functional decline in ALS patients’ motor skills with as measured after 2 months by the ALSFRS-R in the limb and bulbar subscores, but not respiratory subscore. Other short-term effects, increased fatigue and negative impact on QoL, were also verified.

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Early detection and tracking of bulbar changes in ALS via frequent and remote speech analysis

Cited by 47 publications

References 21 publications

Digital Biomarkers for Neuromuscular Disorders: A Systematic Scoping Review

Digital Biomarkers for Neuromuscular Disorders: A Systematic Scoping Review

Biomedical signals and machine learning in amyotrophic lateral sclerosis: a systematic review

Effects of prolonged interruption of rehabilitation routines in amyotrophic lateral sclerosis patients

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