ALS longitudinal studies with frequent data collection at home: study design and baseline data

The Digital Platform and Its Emerging Role in Decentralized Clinical Trials

Decentralized clinical trials (DCTs) are becoming increasingly popular. Digital clinical trial platforms are software environments where users complete designated clinical trial tasks, providing investigators and trial participants with efficient tools to support trial activities and streamline trial processes. In particular, digital platforms with a modular architecture lend themselves to DCTs, where individual trial activities can correspond to specific platform modules. While design features can allow users to customize their platform experience, the real strengths of digital platforms for DCTs are enabling centralized data capture and remote monitoring of trial participants and in using digital technologies to streamline workflows and improve trial management. When selecting a platform for use in a DCT, sponsors and investigators must consider the specific trial requirements. All digital platforms are limited in their functionality and technical capabilities. Integrating additional functional modules into a central platform may solve these challenges, but few commercial platforms are open to integrating third-party components. The lack of common data standardization protocols for clinical trials will likely limit the development of one-size-fits-all digital platforms for DCTs. This viewpoint summarizes the current role of digital platforms in supporting decentralized trial activities, including a discussion of the potential benefits and challenges of digital platforms for investigators and participants. We will highlight the role of the digital platform in the development of DCTs and emphasize where existing technology is functionally limiting. Finally, we will discuss the concept of the ideal fully integrated and unified DCT and the obstacles developers must address before it can be realized.

Exploratory study to evaluate the acceptability of a wearable accelerometer to assess motor progression in motor neuron disease

Motor neuron disease (MND) is a rapidly progressive condition traditionally assessed using a questionnaire to evaluate physical function, the revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R). Its use can be associated with poor sensitivity in detecting subtle changes over time and there is an urgent need for more sensitive and specific outcome measures. The ActiGraph GT9X is a wearable device containing multiple sensors that can be used to provide metrics that represent physical activity. The primary aim of this study was to investigate the initial suitability and acceptability of limb-worn wearable devices to group of people with MND in Scotland. A secondary aim was to explore the preliminary associations between the accelerometer sensor data within the ActiGraph GT9X and established measures of physical function. 10 participants with MND completed a 12-week schedule of assessments including fortnightly study visits, both in-person and over videoconferencing software. Participants wore the device on their right wrist and right ankle for a series of movements, during a 6-min walking test and for a period of 24-h wear, including overnight. Participants also completed an ALSFRS-R and questionnaires on their experience with the devices. 80% of the participants found wearing these devices to be a positive experience and no one reported interference with daily living or added burden. However, 30% of the participants experienced technical issues with their devices. Data from the wearable devices correlated with established measures of physical function.

Automated speech analytics in ALS: higher sensitivity of digital articulatory precision over the ALSFRS-R

Objective: Although studies have shown that digital measures of speech detected ALS speech impairment and correlated with the ALSFRS-R speech item, no study has yet compared their performance in detecting speech changes. In this study, we compared the performances of the ALSFRS-R speech item and an algorithmic speech measure in detecting clinically important changes in speech. Importantly, the study was part of a FDA submission which received the breakthrough device designation for monitoring ALS; we provide this paper as a roadmap for validating other speech measures for monitoring disease progression. Methods: We obtained ALSFRS-R speech subscores and speech samples from participants with ALS. We computed the minimum detectable change (MDC) of both measures; using clinician-reported listener effort and a perceptual ratings of severity, we calculated the minimal clinically important difference (MCID) of each measure with respect to both sets of clinical ratings. Results: For articulatory precision, the MDC (.85) was lower than both MCID measures (2.74 and 2.28), and for the ALSFRS-R speech item, MDC (.86) was greater than both MCID measures (.82 and .72), indicating that while the articulatory precision measure detected minimal clinically important differences in speech, the ALSFRS-R speech item did not. Conclusion: The results demonstrate that the digital measure of articulatory precision effectively detects clinically important differences in speech ratings, outperforming the ALSFRS-R speech item. Taken together, the results herein suggest that this speech outcome is a clinically meaningful measure of speech change.

Operationalizing Clinical Speech Analytics: Moving From Features to Measures for Real-World Clinical Impact

OBJECTIVE

This research note advocates for a methodological shift in clinical speech analytics, emphasizing the transition from high-dimensional speech feature representations to clinically validated speech measures designed to operationalize clinically relevant constructs of interest. The aim is to enhance model generalizability and clinical applicability in real-world settings.

METHOD

We outline the challenges of using conventional supervised machine learning models in clinical speech analytics, particularly their limited generalizability and interpretability. We propose a new framework focusing on speech measures that are closely tied to specific speech constructs and have undergone rigorous validation. This research note discusses a case study involving the development of a measure for articulatory precision in amyotrophic lateral sclerosis (ALS), detailing the process from ideation through Food and Drug Administration (FDA) breakthrough status designation.

RESULTS

The case study demonstrates how the operationalization of the articulatory precision construct into a quantifiable measure yields robust, clinically meaningful results. The measure's validation followed the V3 framework (verification, analytical validation, and clinical validation), showing high correlation with clinical status and speech intelligibility. The practical application of these measures is exemplified in a clinical trial and designation by the FDA as a breakthrough status device, underscoring their real-world impact.

CONCLUSIONS

Transitioning from speech features to speech measures offers a more targeted approach for developing speech analytics tools in clinical settings. This shift ensures that models are not only technically sound but also clinically relevant and interpretable, thereby bridging the gap between laboratory research and practical health care applications. We encourage further exploration and adoption of this approach for developing interpretable speech representations tailored to specific clinical needs.

Contribution of neurophysiology to the diagnosis and monitoring of ALS

This chapter describes the role of neurophysiological techniques in diagnosing and monitoring amyotrophic lateral sclerosis (ALS). Despite many advances, electromyography (EMG) remains a keystone investigation from which to build support for a diagnosis of ALS, demonstrating the pathophysiological processes of motor unit hyperexcitability, denervation and reinnervation. We consider development of the different diagnostic criteria and the role of EMG therein. While not formally recognised by established diagnostic criteria, we discuss the pioneering studies that have demonstrated the diagnostic potential of transcranial magnetic stimulation (TMS) of the motor cortex and highlight the growing evidence for TMS in the diagnostic process. Finally, accurately monitoring disease progression is crucial for the successful implementation of clinical trials. Neurophysiological measures of disease state have been incorporated into clinical trials for over 20 years and we review prominent techniques for assessing disease progression.

Speech timing and monosyllabic diadochokinesis measures in the assessment of amyotrophic lateral sclerosis in Canadian French

PURPOSE

The primary objective of this study was to determine if speech and pause measures obtained using a passage reading task and timing measures from a monosyllabic diadochokinesis (DDK) task differ across speakers of Canadian French diagnosed with amyotrophic lateral sclerosis (ALS) presenting with and without bulbar symptoms, and healthy controls. The secondary objective was to determine if these measures can reflect the severity of bulbar symptoms.

METHOD

A total of 29 Canadian French speakers with ALS (classified as bulbar symptomatic [n = 14] or pre-symptomatic [n = 15]) and 17 age-matched healthy controls completed a passage reading task and a monosyllabic DDK task (/pa/ and /ta/), for up to three follow-up visits. Measures of speaking rate, total duration, speech duration, and pause events were extracted from the passage reading recordings using a semi-automated speech and pause analysis procedure. Manual analysis of DDK recordings provided measures of DDK rate and variability.

RESULT

Group comparisons revealed significant differences (p = < .05) between the symptomatic group and the pre-symptomatic and control groups for all passage measures and DDK rates. Only the DDK rate in /ta/ differentiated the pre-symptomatic and control groups. Repeated measures correlations revealed moderate correlations (rrm = > 0.40; p = < 0.05) between passage measures of total duration, speaking rate, speech duration, and number of pauses, and ALSFRS-R total and bulbar scores, as well as between DDK rate and ALSFRS-R total score.

CONCLUSION

Speech and pause measures in passage and timing measures in monosyllabic DDK tasks might be suitable for monitoring bulbar functional symptoms in French speakers with ALS, but more work is required to identify which measures are sensitive to the earliest stages of the disease.

Draft Guidance for Industry Duchenne Muscular Dystrophy, Becker Muscular Dystrophy, and Related Dystrophinopathies - Developing Potential Treatments for the Entire Spectrum of Disease

Background

Duchenne muscular dystrophy (DMD) and related dystrophinopathies are neuromuscular conditions with great unmet medical needs that require the development of effective medical treatments.

Objective

To aid sponsors in clinical development of drugs and therapeutic biological products for treating DMD across the disease spectrum by integrating advancements, patient registries, natural history studies, and more into a comprehensive guidance.

Methods

This guidance emerged from collaboration between the FDA, the Duchenne community, and industry stakeholders. It entailed a structured approach, involving multiple committees and boards. From its inception in 2014, the guidance underwent revisions incorporating insights from gene therapy studies, cardiac function research, and innovative clinical trial designs.

Results

The guidance provides a deeper understanding of DMD and its variants, focusing on patient engagement, diagnostic criteria, natural history, biomarkers, and clinical trials. It underscores patient-focused drug development, the significance of dystrophin as a biomarker, and the pivotal role of magnetic resonance imaging in assessing disease progression. Additionally, the guidance addresses cardiomyopathy's prominence in DMD and the burgeoning field of gene therapy.

Conclusions

The updated guidance offers a comprehensive understanding of DMD, emphasizing patient-centric approaches, innovative trial designs, and the importance of biomarkers. The focus on cardiomyopathy and gene therapy signifies the evolving realm of DMD research. It acts as a crucial roadmap for sponsors, potentially leading to improved treatments for DMD.

Asynchronous online focus groups for research with people living with amyotrophic lateral sclerosis and family caregivers: usefulness, acceptability and lessons learned

BACKGROUND

People with amyotrophic lateral sclerosis (ALS) face disability- and travel-related barriers to research participation. We investigate the usefulness and acceptability of asynchronous, online focus groups (AOFGs) for research involving people affected by ALS (patients and family caregivers) and outline lessons learned.

METHODS

The ALS Talk Project, consisting of seven AOFGs and 100 participants affected by ALS, provided context for this investigation. Hosted on the secure itracks Board™ platform, participants interacted in a threaded web forum structure. Moderators posted weekly discussion questions and facilitated discussion. Data pertaining to methodology, participant interaction and experience, and moderator technique were analyzed using itracks and NVivo 12 analytics (quantitative) and conventional content analysis and the constant-comparative approach (qualitative).

RESULTS

There was active engagement within groups, with post lengths averaging 111.48 words and a complex network of branching interactions between participants. One third of participant responses included individual reflections without further interaction. Participants affirmed their co-group members, offered practical advice, and discussed shared and differing perspectives. Moderators responded to all posts, indicating presence and probing answers. AOFGs facilitated qualitative and quantitative data-gathering and flexible response to unanticipated events. Although total participation fell below 50% after 10-12 weeks, participants valued interacting with peers in an inclusive, confidential forum. Participants used a variety of personal devices, browsers, and operating systems when interacting on the online platform.

CONCLUSIONS

This methodological examination of AOFGs for patient-centred investigations involving people affected by ALS demonstrates their usefulness and acceptability, and advances knowledge of online research methodologies. Lessons learned include: early identification of research goals and participant needs is critical to selecting an AOFG platform; although duration longer than 10-12 weeks may be burdensome in this population, participants were positive about AOFGs; AOFGs offer real world flexibility enabling response to research challenges and opportunities; and, AOGFs can effectively foster safe spaces for sharing personal perspectives and discussing sensitive topics. With moderators playing an important role in fostering engagement, AOFGs facilitated rich data gathering and promoted reciprocity by fostering the exchange of ideas and interaction between peers. Findings may have implications for research involving other neurologically impaired and/or medically vulnerable populations.

Wav2DDK: Analytical and Clinical Validation of an Automated Diadochokinetic Rate Estimation Algorithm on Remotely Collected Speech

PURPOSE

Oral diadochokinesis is a useful task in assessment of speech motor function in the context of neurological disease. Remote collection of speech tasks provides a convenient alternative to in-clinic visits, but scoring these assessments can be a laborious process for clinicians. This work describes Wav2DDK, an automated algorithm for estimating the diadochokinetic (DDK) rate on remotely collected audio from healthy participants and participants with amyotrophic lateral sclerosis (ALS).

METHOD

Wav2DDK was developed using a corpus of 970 DDK assessments from healthy and ALS speakers where ground truth DDK rates were provided manually by trained annotators. The clinical utility of the algorithm was demonstrated on a corpus of 7,919 assessments collected longitudinally from 26 healthy controls and 82 ALS speakers. Corpora were collected via the participants' own mobile device, and instructions for speech elicitation were provided via a mobile app. DDK rate was estimated by parsing the character transcript from a deep neural network transformer acoustic model trained on healthy and ALS speech.

RESULTS

Algorithm estimated DDK rates are highly accurate, achieving .98 correlation with manual annotation, and an average error of only 0.071 syllables per second. The rate exactly matched ground truth for 83% of files and was within 0.5 syllables per second for 95% of files. Estimated rates achieve a high test-retest reliability (r = .95) and show good correlation with the revised ALS functional rating scale speech subscore (r = .67).

CONCLUSION

We demonstrate a system for automated DDK estimation that increases efficiency of calculation beyond manual annotation. Thorough analytical and clinical validation demonstrates that the algorithm is not only highly accurate, but also provides a convenient, clinically relevant metric for tracking longitudinal decline in ALS, serving to promote participation and diversity of participants in clinical research.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.23787033.

A speech-based prognostic model for dysarthria progression in ALS

Objective: We demonstrated that it was possible to predict ALS patients' degree of future speech impairment based on past data. We used longitudinal data from two ALS studies where participants recorded their speech on a daily or weekly basis and provided ALSFRS-R speech subscores on a weekly or quarterly basis (quarter-annually). Methods: Using their speech recordings, we measured articulatory precision (a measure of the crispness of pronunciation) using an algorithm that analyzed the acoustic signal of each phoneme in the words produced. First, we established the analytical and clinical validity of the measure of articulatory precision, showing that the measure correlated with perceptual ratings of articulatory precision (r = .9). Second, using articulatory precision from speech samples from each participant collected over a 45-90 day model calibration period, we showed it was possible to predict articulatory precision 30-90 days after the last day of the model calibration period. Finally, we showed that the predicted articulatory precision scores mapped onto ALSFRS-R speech subscores. Results: the mean absolute error was as low as 4% for articulatory precision and 14% for ALSFRS-R speech subscores relative to the total range of their respective scales. Conclusion: Our results demonstrated that a subject-specific prognostic model for speech predicts future articulatory precision and ALSFRS-R speech values accurately.

Impact of mode of training and recertification on ALSFRS-R rater performance

OBJECTIVE

The ALS Functional Rating Scale-Revised (ALSFRS-R) is the most frequent primary outcome measure in ALS trials. The reliable and accurate performance of this instrument is critical. The Barrow Neurological Institute Clinical Research Organization (BNI-CRO) has been performing evaluator training and certification for the ALSFRS-R since 2011. Here we evaluate the impact of evaluator training and participant practice.

METHODS

Training records were reviewed for evaluators trained and certified by the BNI-CRO at least twice since 2011. We determined the impact of training intervals on ease of recertification. We also assessed whether the mode of training impacted successful vignette scoring. For self-reported participant assessment, remote training was provided by BNI CRO personnel; we determined whether there was a practice effect on reliable assessment.

RESULTS

117 evaluators completed at least two training sessions either via interactive in-person training, interactive remote training, or by completing a self-training module. Poorer performance on retraining was noted when the interval between pieces of training was 2 years or greater. Mode of training also impacted performance; interactive in-person and remote sessions were associated with better performance than the use of self-training modules. For participant self-assessment, week-week variability in ALSFRS-R scores declined over time as the study progressed.

CONCLUSIONS

Standard training of evaluators has an impact on the performance of the ALSFRS-R, with shorter intervals between training positively impacting performance. Interactive training sessions allowing for real-time questions also are associated with better performance. Continued training is important to maintain a high-quality ALSFRS-R assessment.

Primary lateral sclerosis natural history study - planning, designing, and early enrollment

Introduction/Aims. Primary lateral sclerosis (PLS) is exceedingly rare and has been an enigmatic disease. Recent progress has drastically changed this perception, with early biomarkers being investigated and potential medications for PLS emerging at the preclinical stage. The aim of this paper is to describe a study of PLS natural history and discuss the limitations and proposed solutions to the study of a rare and slowly progressive disease. Methods. The PLS Natural History Study is a 30-site, 24-month, prospective study that is supported by multiple funding sources. The study aims to enroll 50 early PLS (disease duration ≤4 years) and 50 definite PLS (disease duration 4 to 15 years) participants using modified PLS Diagnostic Criteria. Smartphone-based assessments including semi-quantitative and quantitative measures and patient-reported outcomes are utilized. In-person quantitative measures are also completed during site visits. The change in the PLS Functional Rating Scale score is the primary outcome. The study utilizes the NeuroBANK^® patient-centric data capture and management platform. The biostatistical analysis plan has been developed. Results. In one year, 28 participants have been recruited. Enrollment has been much slower than anticipated due to the COVID-19 pandemic, the rarity of PLS, and potential study competition for internal resources from ALS clinical trials. Discussion. We discuss the need for more innovative methods to enroll and study individuals with such rare diseases and propose a number of mechanisms by which more efficient enrollment could be facilitated.

A systematic review of digital technology to evaluate motor function and disease progression in motor neuron disease

Amyotrophic lateral sclerosis (ALS) is the most common subtype of motor neuron disease (MND). The current gold-standard measure of progression is the ALS Functional Rating Scale-Revised (ALS-FRS(R)), a clinician-administered questionnaire providing a composite score on physical functioning. Technology offers a potential alternative for assessing motor progression in both a clinical and research capacity that is more sensitive to detecting smaller changes in function. We reviewed studies evaluating the utility and suitability of these devices to evaluate motor function and disease progression in people with MND (pwMND). We systematically searched Google Scholar, PubMed and EMBASE applying no language or date restrictions. We extracted information on devices used and additional assessments undertaken. Twenty studies, involving 1275 (median 28 and ranging 6-584) pwMND, were included. Sensor type included accelerometers (n = 9), activity monitors (n = 4), smartphone apps (n = 4), gait (n = 3), kinetic sensors (n = 3), electrical impedance myography (n = 1) and dynamometers (n = 2). Seventeen (85%) of studies used the ALS-FRS(R) to evaluate concurrent validity. Participant feedback on device utility was generally positive, where evaluated in 25% of studies. All studies showed initial feasibility, warranting larger longitudinal studies to compare device sensitivity and validity beyond ALS-FRS(R). Risk of bias in the included studies was high, with a large amount of information to determine study quality unclear. Measurement of motor pathology and progression using technology is an emerging, and promising, area of MND research. Further well-powered longitudinal validation studies are needed.

Remote digital assessment of amyotrophic lateral sclerosis functional rating scale - a multicenter observational study

Objective: Remote self-assessment of the revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R) using digital data capture was investigated for its feasibility as an add-on to ALSFRS-R assessments during multidisciplinary clinic visits. Methods: From August 2017 to December 2021, at 12 ALS centers in Germany, an observational study on remote assessment of the ALSFRS-R was performed. In addition to the assessment of ALSFRS-R during clinic visits, patients were offered a digital self-assessment of the ALSFRS-R - either on a computer or on a mobile application ("ALS-App"). Results: An estimated multicenter cohort of 4,670 ALS patients received care at participating ALS centers. Of these patients, 971 remotely submitted the ALSFRS-R, representing 21% of the multicenter cohort. Of those who opted for remote assessment, 53.7% (n = 521) completed a minimum of 4 ALSFRS-R per year with a mean number of 10.9 assessments per year. Different assessment frequencies were found for patients using a computer (7.9 per year, n = 857) and mobile app (14.6 per year, n = 234). Patients doing remote assessments were more likely to be male and less functionally impaired but many patients with severe disability managed to complete it themselves or with a caregiver (35% of remote ALSFRS-R cohort in King's Stage 4). Conclusions: In a dedicated ALS center setting remote digital self-assessment of ALSFRS-R can provide substantial data which is complementary and potentially an alternative to clinic assessments and could be used for research purposes and person-level patient management. Addressing barriers relating to patient uptake and adherence are key to its success.

Patient perspectives on digital healthcare technology in care and clinical trials for motor neuron disease: an international survey

Introduction

To capture the patient’s attitude toward remote monitoring of motor neuron disease (MND) in care and clinical trials, and their concerns and preferences regarding the use of digital technology.

Methods

We performed an international multi-centre survey study in three MND clinics in The Netherlands, the United Kingdom, and Australia. The survey was co-developed by investigators and patients with MND, and sent to patients by e-mail or postal-mail. The main topics included: patients’ attitude towards remote care, participating in decentralized clinical trials, and preferences for and concerns with digital technology use.

Results

In total, 332 patients with MND participated. A majority of patients indicated they would be happy to self-monitor their health from home (69%), be remotely monitored by a multidisciplinary care team (75%), and would be willing to participate in clinical trials from home (65%). Patients considered respiratory function and muscle strength most valuable for home-monitoring. The majority of patients considered the use of at least three devices/apps (75%) once a week (61%) to be acceptable for home-monitoring. Fifteen percent of patients indicated they would not wish to perform home-measurements; reporting concerns about the burden and distress of home-monitoring, privacy and data security.

Conclusion

Most patients with MND exhibited a positive attitude toward the use of digital technology in both care and clinical trial settings. A subgroup of patients reported concerns with home-monitoring, which should be addressed in order to improve widespread adoption of remote digital technology in clinical MND care.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-022-11273-x.

Initiating home spirometry for children during the COVID-19 pandemic - A practical guide

The COVID-19 pandemic has led to a rapid escalation in use of home monitoring and video consultations in children with a variety of chronic respiratory conditions. Our department set up a home spirometry service from scratch once it became evident that we needed to keep patients away from hospital clinics whenever possible. We faced a number of challenges but now have around 400 children using home spirometers. There are a number of portable spirometers available, some with online platforms. The technology, particularly the software/apps interface, has been improved by the companies in response to issues that have arisen. We believe the use of home monitoring is here to stay.

A machine-learning based objective measure for ALS disease severity

Amyotrophic Lateral Sclerosis (ALS) disease severity is usually measured using the subjective, questionnaire-based revised ALS Functional Rating Scale (ALSFRS-R). Objective measures of disease severity would be powerful tools for evaluating real-world drug effectiveness, efficacy in clinical trials, and for identifying participants for cohort studies. We developed a machine learning (ML) based objective measure for ALS disease severity based on voice samples and accelerometer measurements from a four-year longitudinal dataset. 584 people living with ALS consented and carried out prescribed speaking and limb-based tasks. 542 participants contributed 5814 voice recordings, and 350 contributed 13,009 accelerometer samples, while simultaneously measuring ALSFRS-R scores. Using these data, we trained ML models to predict bulbar-related and limb-related ALSFRS-R scores. On the test set (n = 109 participants) the voice models achieved a multiclass AUC of 0.86 (95% CI, 0.85-0.88) on speech ALSFRS-R prediction, whereas the accelerometer models achieved a median multiclass AUC of 0.73 on 6 limb-related functions. The correlations across functions observed in self-reported ALSFRS-R scores were preserved in ML-derived scores. We used these models and self-reported ALSFRS-R scores to evaluate the real-world effects of edaravone, a drug approved for use in ALS. In the cohort of 54 test participants who received edaravone as part of their usual care, the ML-derived scores were consistent with the self-reported ALSFRS-R scores. At the individual level, the continuous ML-derived score can capture gradual changes that are absent in the integer ALSFRS-R scores. This demonstrates the value of these tools for assessing disease severity and, potentially, drug effects.

Telehealth in long-term neurological conditions: the potential, the challenges and the key recommendations

Long-term neurological conditions (LTNCs) cause physical and psychological symptoms that have a significant impact on activities of daily living and quality of life. Multidisciplinary teams are effective at providing treatment for people with LTNCs; however, access to such services by people with disabilities can be difficult and as a result, good quality care is not universal. One potential solution is telehealth. This review describes the potential of telehealth to support people with LTNCs, the challenges of designing and implementing these systems, and the key recommendations for those involved in telehealth to facilitate connected services that can benefit patients, carers and healthcare professionals. These recommendations include understanding the problems posed by LTNCs and the needs of the end-user through a person-centred approach. We discuss how to work collaboratively and use shared learning, and consider how to effectively evaluate the intervention at every stage of the development process.

A post pandemic roadmap toward remote assessment for neuromuscular disorders: limitations and opportunities

Recent advances in technology and expanding therapeutic opportunities in neuromuscular disorders has resulted in greater interest in and development of remote assessments. Over the past year, the rapid and abrupt COVID-19 shutdowns and stay-at-home orders imposed challenges to routine clinical management and clinical trials. As in-person services were severely limited, clinicians turned to remote assessments through telehealth to allow for continued care. Typically, disease-specific clinical outcome assessments (COAs) for neuromuscular disorders (NMD) are developed over many years through rigorous and iterative processes to fully understand their psychometric properties. While efforts were underway towards developing remote assessments for NMD before the pandemic, few if any were fully developed or validated. These included assessments of strength, respiratory function and patient-reported outcomes, as well as wearable technology and other devices to quantify physical activity and function. Without many choices, clinicians modified COAs for a virtual environment recognizing it was not yet known how they compared to standard in-person administration. Despite being able to quickly adapt to the demands of the COVID-19 pandemic, these experiences with remote assessments uncovered limitations and opportunities. It became clear that existing COAs required modifications for use in a virtual environment limiting the interpretation of the information gathered. Still, the opportunity for real-world evaluation and reduced patient burden were clear benefits to remote assessment and may provide a more robust understanding and characterization of disease impact in NMD. Hence, we propose a roadmap navigating an informed post-pandemic path toward development and implementation of safe and successful use of remote assessments for patients with NMD.

Technology-outcome measures in neuromuscular disorders: a systematic review

BACKGROUND

Portable and wearable devices can monitor a number of physical performances and have been lately applied to patients with neuromuscular disorders (NMD).

METHODS

We performed a systematic search of literature databases following PRISMA principles, including all studies reporting the use of technological devices for motor function assessment in NMDs from 2000 to 2021. We also summarized the evidence on measurement properties (validity, reliability, responsiveness) of the analyzed technological outcome measures.

RESULTS

One-hundred studies fulfilled the selection criteria, most of them published in the last ten years. We defined four categories that gathered similar technologies: gait analysis tools, for clinical assessment of pace and posture; continuous monitoring of physical activity with inertial sensors, that allow "unsupervised" activity assessment; upper limb evaluation tools, including Kinect-based outcome measures to assess the reachable workspace; and new muscle strength assessment tools, such as Myotools. Inertial sensors have the evident advantage of being applied in the "in-home" setting, which has become especially appealing with the Covid-19 pandemic, although poor evidence from psychometric property assessment and results of the analyzed studies may limit their research application. Both Kinect-based outcome measures and Myotools have been already validated in multicenter studies and different NMDs, showing excellent characteristics for application in clinical trials.

CONCLUSION

This overview is intended to raise awareness on the potential of the different TOMs in the neuromuscular field and be an informative source for the design of future clinical trials, particularly in the era of telemedicine.

A Systematic Review of Methods used to Conduct Decentralised Clinical Trials

Aims

To evaluate, using quantitative and qualitative approaches, published data on the design and conduct of decentralised clinical trials (DCTs).

Methods

We searched MEDLINE, EMBASE, CENTRAL, PsycINFO, ProQuest Dissertations and Theses, ClinicalTrials.gov, OpenGrey and Google Scholar for publications reporting, discussing, or evaluating decentralised clinical research methods. Reports of randomised clinical trials using decentralised methods were included in a focused quantitative analysis with a primary outcome of number of randomised participants. All publications discussing or evaluating DCTs were included in a wider qualitative analysis to identify advantages, disadvantages, facilitators, barriers and stakeholder opinions of decentralised clinical trials. Quantitative data were summarised using descriptive statistics, and qualitative data analysed using a thematic approach.

Results

Initial searches identified 19 704 articles. After removal of duplicates, 18 553 were screened, resulting in 237 eligible for full‐text assessment. Forty‐five trials were included in the quantitative analysis; 117 documents were included in the qualitative analysis. Trials were widely heterogeneous in design and reporting, precluding meta‐analysis of the effect of DCT methods on the primary recruitment outcome. Qualitative analysis formulated 4 broad themes: value, burden, safety and equity. Participant and stakeholder experiences of DCTs were incompletely represented.

Conclusion

DCTs are developing rapidly. However, there is insufficient evidence to confirm which methods are most effective in trial recruitment, retention, or overall cost. The identified advantages, disadvantages, facilitators and barriers should inform the development of DCT methods. We recommend further research on how DCTs are experienced and perceived by participants and stakeholders to maximise potential benefits.

Correlations between measures of ALS respiratory function: is there an alternative to FVC?

Background: An ongoing longitudinal study in six European sites includes a 3-monthly assessment of forced vital capacity (FVC), slow vital capacity (SVC), peak cough flow (PCF), and Sniff nasal inspiratory pressure (SNIP). The aim of this interim analysis was to assess the potential for SNIP to be a surrogate for aerosol generating procedures given COVID-19 related restrictions. Methods: This was a prospective observational study. Patients attending six study sites with King's Stage 2 or 3 ALS completed baseline FVC/SVC/SNIP/PCF and repeated assessments 3 monthly. Data were collected from March 2018 to March 2020, after which a COVID-19 related study suspension was imposed. Correlations between the measures were calculated. A Bayesian multiple outcomes random-effects model was constructed to investigate rates of decline across measures. Results: In total, 270 cases and 828 assessments were included (Mean age 65.2 ± 15.4 years; 32.6% Female; 60% Kings stage 2; 81.1% spinal onset). FVC and SVC were the most closely correlated outcomes (0.95). SNIP showed the least correlation with other metrics 0.53 (FVC), 0.54 (SVC), 0.60 (PCF). All four measures significantly declined over time. SNIP in the bulbar onset group showed the fastest rate of decline. Discussion: SNIP was not well correlated with FVC and SVC, probably because it examines a different aspect of respiratory function. Respiratory measures declined over time, but differentially according to the site of onset. SNIP is not a surrogate for FVC and SVC, but is a complementary measure, declining linearly and differentiating spinal and bulbar onset patients.

MiNDAUS partnership: a roadmap for the cure and management of motor Neurone disease

An innovative approach to patient management, evidence-based policy development, and clinical drug trials is required to provide personalized care and to improve the likelihood of finding an effective treatment for Motor Neurone Disease (MND). The MiNDAus Partnership builds on and extends existing national collaborations in a targeted approach to improve the standard and coordination of care for people living with MND in Australia, and to enhance the prospects of discovering a cure or treatment. Relationships have been developed between leading clinical and research groups as well as patient-centered organizations, care providers, and philanthropy with a shared vision. MiNDAus has established a corporate structure and meets at least biannually to decide on how best to progress research, drug development, and patient management. The key themes are; (i) empowering patients and their family carers to engage in self-management and ensure personalized service provision, treatment, and policy development, (ii) integration of data collection so as to better inform policy development, (iii) unifying patients and carers with advocacy groups, funding bodies, clinicians and academic institutions so as to inform policy development and research, (iv) coordination of research efforts and development of standardized national infrastructure for conducting innovative clinical MND trials that can be harmonized within Australia and with international trials consortia. Such a collaborative approach is required across stakeholders in order to develop innovative management guidelines, underpinned by necessary and evidence-based policy change recommendations, which, will ensure the best patient care until a cure is discovered.

A Road Map for Remote Digital Health Technology for Motor Neuron Disease

Despite recent and potent technological advances, the real-world implementation of remote digital health technology in the care and monitoring of patients with motor neuron disease has not yet been realized. Digital health technology may increase the accessibility to and personalization of care, whereas remote biosensors could optimize the collection of vital clinical parameters, irrespective of patients’ ability to visit the clinic. To facilitate the wide-scale adoption of digital health care technology and to align current initiatives, we outline a road map that will identify clinically relevant digital parameters; mediate the development of benefit-to-burden criteria for innovative technology; and direct the validation, harmonization, and adoption of digital health care technology in real-world settings. We define two key end products of the road map: (1) a set of reliable digital parameters to capture data collected under free-living conditions that reflect patient-centric measures and facilitate clinical decision making and (2) an integrated, open-source system that provides personalized feedback to patients, health care providers, clinical researchers, and caregivers and is linked to a flexible and adaptable platform that integrates patient data in real time. Given the ever-changing care needs of patients and the relentless progression rate of motor neuron disease, the adoption of digital health care technology will significantly benefit the delivery of care and accelerate the development of effective treatments.

Quantitative muscle ultrasound and electrical impedance myography in late onset Pompe disease: A pilot study of reliability, longitudinal change and correlation with function

Background/objectives

Late-onset Pompe disease (LOPD) is slowly progressive, making it difficult to assess clinical change and response to interventions. In this study, quantitative muscle ultrasonography (QMUS) and electrical impedance myography (EIM) were evaluated as potential biomarkers.

Methods

25 patients with confirmed LOPD were recruited from the Duke Pompe Clinic and evaluated with standard clinical measures, QMUS, standard EIM (sEIM) and hand-held EIM (hEIM). Patients were evaluated at baseline, 12 months and 24 months. MUS, sEIM and hEIM were compared with the clinical data. Five patients were given hEIM devices to perform measurements at home.

Results

QMUS and hEIM had good reliability as measures of muscle structure and conduction properties. Home, patient-performed hEIM measurements did not differ significantly from those performed in the clinic setting. Thirteen patients completed all follow-up measures. Most measures did not change over the study period, however, vastus lateralis echointensity increased 27%, a sign of declining muscle health. Additionally, significant correlations between QMUS, hEIM and measures of muscle strength and function were present.

Conclusions

QMUS and hEIM may provide useful outcome measures for future studies in LOPD with hEIM providing an opportunity to collect data at home. Larger, multicenter studies are needed to explore these possibilities.

Estimation of forced vital capacity using speech acoustics in patients with ALS

In this study, we present and provide validation data for a tool that predicts forced vital capacity (FVC) from speech acoustics collected remotely via a mobile app without the need for any additional equipment (e.g. a spirometer). We trained a machine learning model on a sample of healthy participants and participants with amyotrophic lateral sclerosis (ALS) to learn a mapping from speech acoustics to FVC and used this model to predict FVC values in a new sample from a different study of participants with ALS. We further evaluated the cross-sectional accuracy of the model and its sensitivity to within-subject change in FVC. We found that the predicted and observed FVC values in the test sample had a correlation coefficient of .80 and mean absolute error between .54 L and .58 L (18.5% to 19.5%). In addition, we found that the model was able to detect longitudinal decline in FVC in the test sample, although to a lesser extent than the observed FVC values measured using a spirometer, and was highly repeatable (ICC = 0.92-0.94), although to a lesser extent than the actual FVC (ICC = .97). These results suggest that sustained phonation may be a useful surrogate for VC in both research and clinical environments.

The patient's perspective of remote respiratory assessments during the COVID-19 pandemic

Forced vital capacity (FVC) is an essential respiratory measurement for assessment and monitoring of patients with Amyotrophic Lateral Sclerosis (ALS). Our clinic rapidly implemented remote assessment of FVC after COVID-19 related restrictions on respiratory testing were imposed, using mini-spirometers and video consultation. We sought to evaluate the patient's experiences of performing remote respiratory assessments to guide future development and optimisation of the service. Twenty-five patients completed surveys. The mean age was 65.2 years and average time from diagnosis was 17.04 (2-99) months. Seventy-two percent (n = 18) required help from a caregiver to perform the tests. Ninety-two percent (n = 23) of patients reported that overall, they were satisfied and were happy to continue with remote respiratory assessment. Reducing the number of clinic visits for review and assessment was valued by 92% (n = 23) and reducing the risk associated with COVID-19 was valued by 96% (n = 24). The highest frequency reported as acceptable for performing the remote breathing assessments was monthly (60%, n = 15), followed by every second month (28%, n = 7). Remote respiratory testing is viewed positively by patients. These technologies used in combination with video-consultations and other novel forms of remote monitoring implemented in response to the COVID-19 crisis will continue to be valuable tools for clinical care in future. However, further evaluation of the validity of remote respiratory assessment is required.

Patient reported outcomes in ALS: characteristics of the self-entry ALS Functional Rating Scale-revised and the Activities-specific Balance Confidence Scale

Objective: This study characterized two patient-reported outcome measures (PROMs): a patient-facing adaptation of the revised amyotrophic lateral sclerosis (ALS) Functional Rating Scale ("self-entry ALSFRS-R") and the Activities-specific Balance Confidence (ABC) Scale. Methods: ALS patients presenting to clinic completed PROMs that included (1) the self-entry ALSFRS-R, (2) the Activities-specific Balance Confidence Scale (ABC Scale), and (3) a question about falls. PROM data were compared to one another and to the traditional ALSFRS-R collected by trained evaluators in clinic ("standard ALSFRS-R"). Results: Over the data collection period, 449 ALS patients completed at least one of the three PROMs. Self-entry vs. standard ALSFRS-R total scores (n = 183) had high agreement (intraclass correlation (ICC)=0.81, 95% CI = 0.67, 0.88). Self-entry ALSFRS-R total scores were significantly higher than standard ALSFRS-R total scores (2.3 points, p < 0.001). In a subset of participants who contributed data at two timepoints, the average ALSFRS-R decline was not significantly different between methods (n = 49). ABC scores correlated highly with self-entry and standard ALSFRS-R Gross Motor subdomain scores (Pearson's r = 0.72, p < 0.001 and Pearson's r = 0.76, p < 0.001, respectively; n = 130). ABC score was negatively correlated with the number of reported falls within the last month (Spearman's r=-0.40; p < 0.001; n = 130). A 10-point decrease in ABC score increased odds of a reported fall by 16%. Conclusions: In a multidisciplinary clinic setting, self-entry and standard ALSFRS-R scores were similar, but not interchangeable. Self-entry scores were higher than standard ALSFRS-R scores but declined at a similar rate to the standard ALSFRS-R. ABC scores correlated with self-reported fall history and thus may provide useful data for clinical care.

Improving clinical trial outcomes in amyotrophic lateral sclerosis

Individuals who are diagnosed with amyotrophic lateral sclerosis (ALS) today face the same historically intransigent problem that has existed since the initial description of the disease in the 1860s - a lack of effective therapies. In part, the development of new treatments has been hampered by an imperfect understanding of the biological processes that trigger ALS and promote disease progression. Advances in our understanding of these biological processes, including the causative genetic mutations, and of the influence of environmental factors have deepened our appreciation of disease pathophysiology. The consequent identification of pathogenic targets means that the introduction of effective therapies is becoming a realistic prospect. Progress in precision medicine, including genetically targeted therapies, will undoubtedly change the natural history of ALS. The evolution of clinical trial designs combined with improved methods for patient stratification will facilitate the translation of novel therapies into the clinic. In addition, the refinement of emerging biomarkers of therapeutic benefits is critical to the streamlining of care for individuals. In this Review, we synthesize these developments in ALS and discuss the further developments and refinements needed to accelerate the introduction of effective therapeutic approaches.

A Bioimpedance-Based Device to Assess the Volume Conduction Properties of the Tongue in Neurological Disorders Affecting Bulbar function

Goal: Current instruments for bulbar assessment exhibit technical limitations that hinder the execution of clinical studies. The volume conduction properties (VCP) of the tongue reflect ionic content and myofiber integrity and they can serve as a new biomarker for evaluating neurological disorders with bulbar dysfunction. Methods: We designed a standalone bioimpedance measurement system that enables accurate, multi-frequency measurement of tongue anisotropic VCP including conductivity and relative permittivity. The system includes a tongue depressor with 16 non-invasive surface sensors for electrical contact with the tongue at directions 0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$^{\circ }$\end{document}, 45\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$^{\circ }$\end{document}, 90\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$^{\circ }$\end{document} and 150\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$^{\circ }$\end{document}. The depressor is interfaced with the tongue electronic system with Bluetooth connectivity, and a smartphone application. De-identified patient data is sent by email. Results: We first determined the accuracy of the hardware performing phantom measurements mimicking a broad range of tongue values and determined the error to be \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$< $\end{document}1%. We then validated our new technology measuring a cohort of 7 healthy human subjects under Institutional Review Board approval. Conclusions: None of the subjects who participated suffered discomfort or gag reflexes. The novel technique presented for intra-oral assessment of tongue VCP provides standard, objective and quantitative data potentially sensitive to alterations in tongue internal structure and composition.

Cognitive Performance of Patients with Adult 5q-Spinal Muscular Atrophy and with Amyotrophic Lateral Sclerosis

Motor neuron diseases, such as spinal muscular atrophy (SMA) and amyotrophic lateral sclerosis (ALS), share several clinical similarities while differing substantially in etiology, disease onset and progression. Cognitive dysfunction, a clinically relevant non-motor feature in a substantial proportion of ALS patients, has been less frequently investigated in SMA. In this prospective multicenter cross-sectional study, cognitive function was assessed by the Edinburgh Cognitive (and Behavioural) ALS Screen (ECAS) and a German vocabulary test (Wortschatztest, WST) in 34 adult patients with SMA types 2-4 and in 34 patients with ALS. Demographic and clinical parameters were assessed to identify factors that potentially influence cognitive function. While SMA and ALS patients were comparable in the vocabulary test, on average, SMA patients performed better than ALS patients in the cognitive domains of memory, language and executive function. Better cognitive abilities in SMA patients seemed to be related to the early onset, rather than the extent or the duration, of their physical handicap. Future studies should focus on disease-specific cognitive functions in SMA.

Portable fixed dynamometry: towards remote muscle strength measurements in patients with motor neuron disease

Background

We aimed to determine (1) the test–retest reliability of a newly developed portable fixed dynamometer (PFD) as compared to the hand-held dynamometer (HHD) in patients with motor neuron disease (MND) and (2) the PFD’s ability to reduce possible examiner-induced ceiling effects.

Methods

Test–retest reliability of isometric muscle strength of the quadriceps was measured in patients with MND and non-neurological controls using the HHD and PFD. Reliability was estimated by the intraclass correlation coefficient (ICC) and standard error of measurement (SEM) using linear mixed effects models, and the Bland–Altman method of agreement.

Results

In total, 45 patients with MND and 43 healthy controls were enrolled in this study. The ICC of the PFD was excellent and similar in both patients and controls (ICC _Patients 99.5% vs. ICC _Controls 98.6%) with a SEM of 6.2%. A strong examiner-induced ceiling effect in HHD was found when the participant’s strength exceeded that of examiner. Employing the PFD increased the range of muscle strength measurements across individuals nearly twofold from 414 to 783 N.

Conclusions

Portable fixed dynamometry may significantly reduce examiner-induced ceiling effects, optimize the standardization of muscle strength testing, and maximize reliability. Ultimately, PFD may improve the delivery of care due to its potential for unsupervised, home-based assessments and reduce the burden to the patient of participating in clinical trials for MND or other neuromuscular diseases.

Repeatability of Commonly Used Speech and Language Features for Clinical Applications

Introduction

Changes in speech have the potential to provide important information on the diagnosis and progression of various neurological diseases. Many researchers have relied on open-source speech features to develop algorithms for measuring speech changes in clinical populations as they are convenient and easy to use. However, the repeatability of open-source features in the context of neurological diseases has not been studied.

Methods

We used a longitudinal sample of healthy controls, individuals with amyotrophic lateral sclerosis, and individuals with suspected frontotemporal dementia, and we evaluated the repeatability of acoustic and language features separately on these 3 data sets.

Results

Repeatability was evaluated using intraclass correlation (ICC) and the within-subjects coefficient of variation (WSCV). In 3 sets of tasks, the median ICC were between 0.02 and 0.55, and the median WSCV were between 29 and 79%.

Conclusion

Our results demonstrate that the repeatability of speech features extracted using open-source tool kits is low. Researchers should exercise caution when developing digital health models with open-source speech features. We provide a detailed summary of feature-by-feature repeatability results (ICC, WSCV, SE of measurement, limits of agreement for WSCV, and minimal detectable change) in the online supplementary material so that researchers may incorporate repeatability information into the models they develop.

New technologies and Amyotrophic Lateral Sclerosis - Which step forward rushed by the COVID-19 pandemic?

Amyotrophic Lateral Sclerosis (ALS) is a fast-progressive neurodegenerative disease leading to progressive physical immobility with usually normal or mild cognitive and/or behavioural involvement. Many patients are relatively young, instructed, sensitive to new technologies, and professionally active when developing the first symptoms. Older patients usually require more time, encouragement, reinforcement and a closer support but, nevertheless, selecting user-friendly devices, provided earlier in the course of the disease, and engaging motivated carers may overcome many technological barriers. ALS may be considered a model for neurodegenerative diseases to further develop and test new technologies. From multidisciplinary teleconsults to telemonitoring of the respiratory function, telemedicine has the potentiality to embrace other fields, including nutrition, physical mobility, and the interaction with the environment. Brain-computer interfaces and eye tracking expanded the field of augmentative and alternative communication in ALS but their potentialities go beyond communication, to cognition and robotics. Virtual reality and different forms of artificial intelligence present further interesting possibilities that deserve to be investigated. COVID-19 pandemic is an unprecedented opportunity to speed up the development and implementation of new technologies in clinical practice, improving the daily living of both ALS patients and carers. The present work reviews the current technologies for ALS patients already in place or being under evaluation with published publications, prompted by the COVID-19 pandemic.

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

Bulbar deterioration in amyotrophic lateral sclerosis (ALS) is a devastating characteristic that impairs patients' ability to communicate, and is linked to shorter survival. The existing clinical instruments for assessing bulbar function lack sensitivity to early changes. In this paper, using a cohort of N = 65 ALS patients who provided regular speech samples for 3-9 months, we demonstrated that it is possible to remotely detect early speech changes and track speech progression in ALS via automated algorithmic assessment of speech collected digitally.

Differential Diagnosis of Apraxia of Speech in Children and Adults: A Scoping Review

Purpose Despite having distinct etiologies, acquired apraxia of speech (AOS) and childhood apraxia of speech (CAS) share the same central diagnostic challenge (i.e., isolating markers specific to an impairment in speech motor planning/programming). The purpose of this review was to evaluate and compare the state of the evidence on approaches to differential diagnosis for AOS and CAS and to identify gaps in each literature that could provide directions for future research aimed to improve clinical diagnosis of these disorders. Method We conducted a scoping review of literature published between 1997 and 2019, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines. For both AOS and CAS, literature was charted and summarized around four main methodological approaches to diagnosis: speech symptoms, quantitative speech measures, impaired linguistic-motor processes, and neuroimaging. Results Results showed that similar methodological approaches have been used to study differential diagnosis of apraxia of speech in adults and children; however, the specific measures that have received the most research attention differ between AOS and CAS. Several promising candidate markers for AOS and CAS have been identified; however, few studies report metrics that can be used to assess their diagnostic accuracy. Conclusions Over the past two decades, there has been a proliferation of research identifying potential diagnostic markers of AOS and CAS. In order to improve clinical diagnosis of AOS and CAS, there is a need for studies testing the diagnostic accuracy of multiple candidate markers, better control over language impairment comorbidity, more inclusion of speech-disordered control groups, and an increased focus on translational work moving toward clinical implementation of promising measures.

Robust Estimation of Hypernasality in Dysarthria with Acoustic Model Likelihood Features

Hypernasality is a common characteristic symptom across many motor-speech disorders. For voiced sounds, hypernasality introduces an additional resonance in the lower frequencies and, for unvoiced sounds, there is reduced articulatory precision due to air escaping through the nasal cavity. However, the acoustic manifestation of these symptoms is highly variable, making hypernasality estimation very challenging, both for human specialists and automated systems. Previous work in this area relies on either engineered features based on statistical signal processing or machine learning models trained on clinical ratings. Engineered features often fail to capture the complex acoustic patterns associated with hypernasality, whereas metrics based on machine learning are prone to overfitting to the small disease-specific speech datasets on which they are trained. Here we propose a new set of acoustic features that capture these complementary dimensions. The features are based on two acoustic models trained on a large corpus of healthy speech. The first acoustic model aims to measure nasal resonance from voiced sounds, whereas the second acoustic model aims to measure articulatory imprecision from unvoiced sounds. To demonstrate that the features derived from these acoustic models are specific to hypernasal speech, we evaluate them across different dysarthria corpora. Our results show that the features generalize even when training on hypernasal speech from one disease and evaluating on hypernasal speech from another disease (e.g., training on Parkinson's disease, evaluation on Huntington's disease), and when training on neurologically disordered speech but evaluating on cleft palate speech.

Improved ALS clinical trials through frequent at-home self-assessment: a proof of concept study

OBJECTIVE

To determine the potential for improving amyotrophic lateral sclerosis (ALS) clinical trials by having patients or caregivers perform frequent self-assessments at home.

METHODS AND PARTICIPANTS

We enrolled ALS patients into a nonblinded, longitudinal 9-month study in which patients and caregivers obtained daily data using several different instruments, including a slow-vital capacity device, a hand grip dynamometer, an electrical impedance myography-based fitness device, an activity tracker, a speech app, and the ALS functional rating scale-revised. Questions as to acceptability were asked at two time points.

RESULTS

A total of 113 individuals enrolled, with 61 (43 men, 18 women, mean age 60.1 ± 9.9 years) collecting a minimum of 7 days data and being included in the analysis. Daily measurements resulted in more accurate assessments of the slope of progression of the disease, resulting in smaller sample size estimates for a hypothetical clinical trial. For example, by performing daily slow-vital capacity measurements, calculated sample size was reduced to 182 subjects/study arm from 882/arm for monthly measurements. Similarly, performing the ALS functional rating scale weekly rather than monthly led to a calculated sample size of 73/arm as compared to 274/arm. Participants generally found the procedures acceptable and, for many, improved their sense of control of their disease.

INTERPRETATION

Frequent at-home measurements using standard tools holds the prospect of tracking progression and reducing sample size requirements for clinical trials in ALS while also being acceptable to the patients. Future studies in this and other neurological disorders should consider adopting this approach to data collection.

The Use of Telehealth to Enhance Care in ALS and other Neuromuscular Disorders

Telehealth has the potential to improve the efficiency of healthcare while reducing the burden on patients and caregivers. Encounters can be synchronous or asynchronous. When used for care of those with amyotrophic lateral sclerosis (ALS) by individual health care providers or by a multidisciplinary team, synchronous telehealth is feasible, acceptable, may produce outcomes comparable to those of in-person care, and is cost effective. Individuals with ALS who use telehealth tend to have lower physical and respiratory function and to live farther from an ALS clinic than those who exclusively attend in-person clinic visits. Asynchronous telehealth can be used as a substitute full multidisciplinary visits, or for remote monitoring of pulmonary function, gait/falls, and speech. Barriers to implementing telehealth on a wider scale include disparities in access to technology and challenges surrounding medical licensure and billing, but these are being addressed.

Validation of the portable Bluetooth® Air Next spirometer in patients with different respiratory diseases

BACKGROUND

Chronic respiratory diseases constitute a considerable part in the practice of pulmonologists and primary care physicians; spirometry is integral for the diagnosis and monitoring of these diseases, yet remains underutilized. The Air Next spirometer (NuvoAir, Sweden) is a novel ultra-portable device that performs spirometric measurements connected to a smartphone or tablet via Bluetooth®.

METHODS

The objective of this study was to assess the accuracy and validity of these measurements by comparing them with the ones obtained with a conventional desktop spirometer. Two hundred subjects were enrolled in the study with various spirometric patterns (50 patients with asthma, 50 with chronic obstructive pulmonary disease and 50 with interstitial lung disease) as well as 50 healthy individuals.

RESULTS

For the key spirometric parameters in the interpretation of spirometry, i.e. FEV1, FVC, FEV1/FVC and FEF25-75%, Pearson correlation and Interclass Correlation Coefficient were greater than 0.94, exhibiting perfect concordance between the two spirometers. Similar results were observed in an exploratory analysis of the subgroups of patients. Using Bland-Altman plots we have shown good reproducibility in the measurements between the two devices, with small mean differences for the evaluated spirometric parameters and the majority of measurements being well within the limits of agreement.

CONCLUSIONS

Our results support the use of Air Next as a reliable spirometer for the screening and diagnosis of various spirometric patterns in clinical practice.

OBJECTIVE ASSESSMENT OF VOCAL TREMOR

Detecting early signs of neurodegeneration is vital for planning treatments for neurological diseases. Speech plays an important role in this context because it has been shown to be a promising early indicator of neurological decline, and because it can be acquired remotely without the need for specialized hardware. Typically, symptoms are characterized by clinicians using subjective and discrete scales. The poor resolution and subjectivity of these scales can make the earliest speech changes hard to detect. In this paper, we propose an algorithm for the objective assessment of vocal tremor, a phenomenon associated with many neurological disorders. The algorithm extracts and aggregates a feature set from the average spectra of the energy and fundamental frequency profiles of a sustained phonation. We show that the resultant low-dimensional feature set reliably classifies healthy controls and patients with amyotrophic lateral sclerosis perceptually rated for tremor by speech language pathologists.

Accelerometry for remote monitoring of physical activity in amyotrophic lateral sclerosis: a longitudinal cohort study

Background

The extensive heterogeneity between patients with amyotrophic lateral sclerosis (ALS) complicates the quantification of disease progression. In this study, we determine the value of remote, accelerometer-based monitoring of physical activity in patients with ALS.

Methods

This longitudinal cohort study was conducted in a home-based setting; all study materials were sent by mail. Patients wore the ActiGraph during waking hours for 7 days every 2–3 months and provided information regarding their daily functioning (ALSFRS-R). We defined four accelerometer-based endpoints that either reflect the average daily activity or quantify the patient’s physical capacity.

Results

A total of 42 patients participated; the total valid monitoring period was 9288 h with a 93.0% adherence rate. At baseline, patients were active 27.9% (range 11.6–52.4%) of their time; this declined by 0.64% (95% 0.43–0.86, p < 0.001) per month. Accelerometer-based endpoints were strongly associated with the ALSFRS-R (r 0.78, 95% CI 0.63–0.92, p < 0.001), but showed less variability over time than the ALSFRS-R (coefficient of variation 0.64–0.81 vs. 1.06, respectively). Accelerometer-based endpoints could reduce sample size by 30.3% for 12-month trials and 44.6% for 18-month trials; for trials lasting less than 9 months, the ALSFRS-R resulted in smaller sample sizes.

Conclusion

Accelerometry is an objective method for quantifying disease progression, which could obtain real-world insights in the patient’s physical functioning and may personalize the delivery of care. In addition, remote monitoring provides patients with the opportunity to participate in clinical trials from home, paving the way to a patient-centric clinical trial model.