Remote Home Assessment of Patients With Amyotrophic Lateral Sclerosis
- Disease/Condition
- Amyotrophic Lateral Sclerosis
- Study type
- Observational
- Primary sponsor
- King's College London
- Location
- London, United Kingdom
- Phase
- N/A
- Start date
- Oct 24, 2022
- End date
- Feb 01, 2024
- Enrollment
- 20 participants
EMG activity
The goal of this observational study is the develop new ways of remotely monitoring the
 health and symptoms of people living with amyotrophic lateral sclerosis from within their
 homes. The main questions it aims to answer are:
 
 - Can we integrate a new muscle monitoring device into Imperial College London's home
 monitoring platform?
 
 - Can we investigate and understand the relationship between muscle activity and measure
 of patient behaviour (e.g., patient movement), physiology (e.g., pulse/blood pressure
 variation) and sleep quality from the home?
 
 - Can we establish a home-based multimodal biomarker that tracks the neurodegenerative
 process in ALS? Participants will have passive internet-of-things sensors and
 internet-enabled medical devices installed in their homes for one year. Some sensors
 will record automatically without any interaction from the participants, but some will
 require participants to engage with daily (e.g., blood pressure monitor) on their own or
 with the help of a study partner.
 
 Where possible, researchers will compare the collected data to other neurodegenerative
 diseases and healthy controls to understand differences over time.
- Registry
- ClinicalTrials.gov
- Trial ID
- NCT06046599
- Type
- Non-Device Trial
Access comprehensive clinical trial information for NCT06046599 through Pure Global AI's free database. This phase not specified trial is sponsored by King's College London and is currently Recruiting. The study focuses on Amyotrophic Lateral Sclerosis. Target enrollment is 20 participants.
This page provides complete trial specifications, intervention details, outcomes, and location information. Pure Global AI offers free access to ClinicalTrials.gov data, helping medical device and pharmaceutical companies navigate clinical research efficiently.