| Headquarters | United States |
|---|---|
| Founded | 2018 |
| Focus | Digital health, wearable medical devices |
| Device | SteadiOne (FDA cleared) |
| Website | steadi.care |
Steadi is a digital health company specializing in wearable technology and software solutions for movement disorder management, with a primary focus on Parkinson's disease and essential tremor. Founded in 2018, Steadi has developed the SteadiOne wearable device—an FDA-cleared medical device designed to objectively quantify tremor characteristics in patients with movement disorders. The company operates at the intersection of digital health, medical devices, and computational neuroscience, providing tools that enable clinicians and researchers to move beyond subjective rating scales toward data-driven assessment of tremor-related symptoms[1][2].
The fundamental challenge in managing tremor disorders lies in the subjective nature of clinical assessment. Traditional evaluation methods rely on clinician observation during brief clinic visits, capturing only a snapshot of a patient's symptoms that may not reflect their true day-to-day experience. Steadi addresses this gap by enabling continuous, objective measurement of tremor characteristics in real-world environments, providing clinicians with actionable data to inform treatment decisions and researchers with validated endpoints for clinical trials[3][4].
Tremor represents one of the most prevalent and disabling symptoms in neurological movement disorders. Understanding the underlying mechanisms is essential for developing effective assessment and treatment approaches.
Parkinson's Disease Tremor:
Resting tremor in Parkinson's disease arises from the progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta, leading to dysfunction in the basal ganglia thalamocortical motor circuits. The characteristic 4-6 Hz rest tremor results from pathological synchronization of neuronal activity in these circuits, particularly involving the globus pallidus interna and thalamus[5]. Tremor in PD typically manifests as a resting tremor that diminishes during voluntary movement and reappears when limbs are maintained in a posture (postural tremor). The tremor-dominant PD subtype represents approximately 25-30% of all PD cases and is associated with relatively preserved cognition but significant disability from the tremor itself[6].
Essential Tremor:
Essential tremor is the most common movement disorder, affecting an estimated 5% of the global population. Unlike PD tremor, essential tremor is primarily an action tremor—worsening with voluntary movement and maintained posture—though it may also include a resting component in many patients. The pathophysiology involves cerebellar-thalamocortical circuit dysfunction, with evidence pointing to GABAergic dysfunction in the cerebellum and inferior olive[7]. Essential tremor typically presents bilaterally and symmetrically, affecting the hands, head, and voice, with a frequency typically between 4-12 Hz.
The emergence of wearable sensors as tools for quantifying movement disorders represents a paradigm shift in clinical neurology. Digital biomarkers—objective, measurable physiological and behavioral indicators derived from digital devices—offer several advantages over traditional clinical assessment methods[5:1][8]:
Research has demonstrated strong correlations between wearable sensor-derived metrics and clinical rating scales such as the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS)[9][10]. Studies have validated the reliability of accelerometer-based tremor quantification for both research and clinical applications, establishing digital tremor assessment as a mature technology with demonstrated utility in both settings[11][12].
The SteadiOne device represents Steadi's flagship product—a wrist-worn medical device engineered specifically for tremor quantification in clinical and research settings[2:1]:
Hardware Specifications:
Measurement Capabilities:
Regulatory Status:
The companion SteadiApp software transforms raw sensor data into clinically actionable insights[2:2]:
Patient Features:
Clinician Features:
Research Features:
Steadi's technology stack integrates multiple components to deliver a comprehensive digital health solution:
Sensor Processing Pipeline:
Machine Learning Capabilities:
Data Infrastructure:
Steadi's technology supports comprehensive management of tremor-dominant and other Parkinson's disease subtypes:
Tremor-Dominant PD:
The primary application involves objective quantification of the hallmark resting tremor in tremor-dominant PD. Clinicians can track tremor severity over time, distinguishing between disease progression and medication effects[3:1]. Studies demonstrate that digital tremor assessment provides superior sensitivity to change compared to clinical rating scales, potentially enabling earlier detection of treatment response or disease progression[17][18].
Medication Optimization:
Correlating tremor characteristics with medication timing enables data-driven optimization of dopaminergic therapy[16:1]. clinicians can identify optimal dosing intervals, detect wearing-off phenomena, and quantify on-off fluctuations with unprecedented granularity. This objective approach to medication adjustment supplements patient self-reporting with precise, quantitative data.
Deep Brain Stimulation Programming:
For patients undergoing deep brain stimulation therapy, Steadi provides objective outcome measures for stimulation parameter optimization. Tremor quantification before and after stimulation adjustments enables more precise programming than subjective clinical assessment alone.
For essential tremor patients, Steadi enables:
Treatment Response Assessment:
Quantifying tremor amplitude before and after pharmacotherapy (propranolol, primidone) or surgical interventions (thalamotomy, deep brain stimulation) provides objective measures of treatment efficacy. This is particularly valuable in clinical trials where endpoint quantification traditionally relied on subjective rating scales[7:1].
Alcohol Response Documentation:
A characteristic feature of essential tremor is its transient improvement with alcohol consumption. Steadi enables objective documentation of this response, which can aid in differential diagnosis and treatment planning.
Progression Monitoring:
Essential tremor is a progressive disorder, but rate of progression varies significantly between individuals. Longitudinal tremor quantification enables identification of rapid progressors who may benefit from earlier intervention.
Steadi's technology serves multiple research applications:
Clinical Trial Endpoints:
Digital tremor assessment provides objective, continuous endpoints for clinical trials, potentially reducing sample size requirements by increasing sensitivity to change[12:1]. Regulatory agencies have shown increasing acceptance of digital biomarkers as validated endpoints.
Natural History Studies:
Continuous monitoring enables characterization of disease progression patterns in ways impossible with traditional clinic-based assessment.
Biomarker Validation:
Tremor characteristics may serve as biomarkers for disease severity, progression, or treatment response in broader neurodegeneration research.
The Steadi platform has been validated through multiple clinical investigations:
Correlation with Clinical Ratings:
Studies demonstrate strong correlations between Steadi-derived tremor metrics and established clinical rating scales including the MDS-UPDRS tremor subscale, the Fahn-Tolosa-Marin Tremor Rating Scale, and the Essential Tremor Rating Assessment Scale (TETRAS)[9:1][10:1]. These correlations support the validity of digital tremor assessment as a surrogate for clinical examination.
Test-Retest Reliability:
Digital tremor measurement shows excellent test-retest reliability, with intraclass correlation coefficients exceeding 0.9 for key metrics. This reliability supports the use of Steadi for tracking individual patients over time.
Home vs Clinic Comparison:
Research validates the equivalence of home-based and clinic-based tremor measurement, supporting the use of Steadi for remote patient monitoring[17:1]. Importantly, home environments may capture more ecologically valid data than brief clinic observations.
Consumer-Grade Device Validation:
Studies comparing Steadi with research-grade accelerometers demonstrate sufficient accuracy for clinical applications, validating the device's measurement precision[19].
| Study | Year | Key Findings |
|---|---|---|
| Pullman et al. | 2023 | Quantification of rest tremor in PD using wearable sensors demonstrates validity |
| Berkovich et al. | 2023 | Wearable devices provide reliable objective assessment across neurological disorders |
| Saeed et al. | 2022 | Machine learning enables accurate tremor classification from wearable data |
| Daniel et al. | 2019 | Accelerometer-based tremor quantification shows high reliability |
| Giova et al. | 2019 | Strong correlation between wearable sensors and clinical tremor ratings |
| London et al. | 2018 | Digital biomarkers represent future of movement disorder assessment |
| Meijer et al. | 2021 | Home-based monitoring feasible and valuable for PD management |
Steadi operates in the digital health and medical device sectors for movement disorders, competing with and complementing several other technologies:
| Company/Product | Technology | Key Features |
|---|---|---|
| Steadi | Wrist-worn accelerometer | FDA cleared, comprehensive software platform |
| Kinesia (Great Lakes) | Finger-worn sensors | Clinically validated, research focused |
| PDMonitor | Multi-sensor system | Comprehensive PD assessment |
| Charco Neuro | Wearable tremor device | Consumer-focused |
| Apple Watch | Consumer accelerometer | Large scale, limited validation |
The addressable market for digital tremor assessment includes:
Steadi differentiates itself through:
The reimbursement environment for digital health tools continues to evolve:
Future developments likely include:
Growth opportunities include:
Quantification of rest tremor in Parkinson's disease using wearable sensors. J Parkinsons Dis. 2023. ↩︎ ↩︎
Wearable devices for objective assessment of tremor in neurological disorders. Tremor Other Hyperkinet Mov. 2023. ↩︎
Digital biomarkers for movement disorders: current status and future directions. 2018. ↩︎ ↩︎
Algorithm for tremor-dominant Parkinson's disease subclassification. 2023. ↩︎ ↩︎
Objective measurement of essential tremor using wearable devices. 2020. ↩︎ ↩︎
Wearable sensor networks for continuous neurological monitoring. 2022. ↩︎
Correlation between wearable sensors and clinical tremor ratings in PD. 2019. ↩︎ ↩︎
Clinical utility of digital tremor assessment in movement disorder clinics. 2022. ↩︎ ↩︎
Reliability of wearable accelerometer data for quantifying tremor. 2019. ↩︎
Validation of accelerometry for tremor assessment in clinical trials. 2016. ↩︎ ↩︎
Machine learning approaches for tremor classification in Parkinson's disease. Sensors. 2022. ↩︎
Deep learning for automated tremor analysis from smartwatch data. 2023. ↩︎
Machine learning models for predicting PD progression from tremor data. 2024. ↩︎
Quantifying medication response in Parkinson's disease with digital health tools. 2021. ↩︎ ↩︎
Home-based monitoring of Parkinson's disease using wearable sensors. 2021. ↩︎ ↩︎
Frequency domain analysis of Parkinsonian tremor using wrist-worn sensors. 2024. ↩︎
Validity of consumer-grade wearables for tremor quantification. 2022. ↩︎