Neuromotus EMG decoding restores thumb and wrist movement

AI system

System: Myoelectric motor execution with sensory training: Neuromotus 8-channel EMG and LDA classifier driving virtual limbs and serious games
Model: A classifier based on linear discriminant analysis.
Release: Exact release not established.
Application developer: Center for Bionics and Pain Research / University of Gothenburg (academic clinical team); device by Integrum AB
Role: The classifier decoded intended movements from muscle signals and controlled a virtual limb.
Configuration: The Neuromotus system used a classifier based on linear discriminant analysis.
Inputs and outputs: Not assessed
Autonomy: Not assessed
Workflow: Residual EMG detectable in the impaired limb. Classifier trained on the patient's own signals each session. Repeated sessions with virtual-limb and game feedback.
Human oversight: Not assessed
Relation to AI: The LDA classifier decodes intended movements from weak EMG in a hand and wrist with no active motion. That is the only way the patient could receive real-time feedback on his motor attempts. The authors attribute the regained movement to this motor execution training. Two authors hold a pending patent on the technology.
AI contribution: The LDA classifier decodes intended movements from weak EMG in a hand and wrist with no active motion. That is the only way the patient could receive real-time feedback on his motor attempts. The authors attribute the regained movement to this motor execution training. Two authors hold a pending patent on the technology.

Benefits

Outcome identifiers: Not assessed
Benefit: active thumb extension (4 degrees) and active wrist flexion (6 degrees)
Category: Improved Physical Health
Status: Not assessed
Beneficiary groups: People. Society.
Beneficiaries: Not assessed
Reach: Not assessed
Distribution and access: Not assessed
Duration: Not assessed
Expected?: Yes
Costs and harms: Not assessed

Measurement

Studies: Not assessed
Study design: Not assessed
Measurement: Not assessed
Setting and sample: Not assessed
Measures: active thumb extension (4 degrees) and active wrist flexion (6 degrees)
Comparison: the arm's function before treatment, after conventional rehabilitation
Results: Reference: no active movement prior the MME interventions. Result: active extension of the thumb (4 degrees) and regained active wrist movement (flex: 6 degrees, extend: 10 degrees).
Additional value from AI: Not assessed
Limitations: Not assessed
Denominators: Not assessed
Materials for replication: Not assessed

Money

Kind of value: Not assessed
Amount: Not assessed
Currency and prices: Not assessed
Period and unit: Not assessed
Realization: Not assessed
Recipients and payers: Not assessed
Gross or net: Not assessed
Included costs: Not assessed
Comparison: Not assessed
Method: Not assessed
Return and payback: Not assessed

People and places

Participants: Developer: Center for Bionics and Pain Research / University of Gothenburg (academic clinical team); device by Integrum AB. Operator: Center for Bionics and Pain Research and Sahlgrenska University Hospital (C.A.R.E.), Mölndal; treatment site not named in the paper.
Jurisdictions: Benefit: Mölndal, Sweden. Developer: Sweden. Operator: Sweden.
Ownership and control: Not assessed
Dependencies: Not assessed
Cross-border connections: Not assessed
Geopolitical implications: Not assessed

Follow-up

Conditions for replication: Intact or reinnervated muscle producing separable EMG patterns. Clinician-run sessions several times a week. Patient motivation to attempt movements without visible motion.
Replication attempts: 1 follow-up entries. Benefit recurred: 1.
Later findings: No follow-up beyond the final session is reported.
Availability: Not assessed
Institutional decision: Not assessed
Grounds: Not assessed
Action and result: Not assessed
Success criterion: Not assessed

Evidence

Source numbers: AIBD-0055-source-0001–0003
Citations: Numbered references below.
Language: Not assessed
Source relationships: Developer
Original evidence: Not assessed
Access and versions: Not assessed
Supported findings: Not assessed
Evidence links: Not assessed
Evidence strength: Not assessed
Missing evidence: Not assessed

Grades

Assessed benefits: People. Society.
Depth: People: 2. Society: 1.
Reasons: People: An identifiable patient regained active thumb and wrist movement conventional rehabilitation had not produced. Gains are small and pain did not consistently improve. Society: Single case; authors present it as a potential treatment needing further study.
Observed or intended: Not assessed
Rubric: Not assessed
Assessor and date: Not assessed
Alternative assessments: Not assessed
Fill: The makers' claim

Entry details

Kind: Not assessed
Related entries: Not assessed
Field: Rehabilitation medicine / hand surgery. Patients with replanted or transplanted limbs.
Purpose: Rehabilitate a highly impaired replanted arm and reduce neuropathic pain using decoded motor intention as feedback
Dates: Date basis unassessed: 2024 (precision unassessed). Updated: 21 October 2026.
Stage: Not assessed
Version: SHA-256: 8f82e8810e83…

References

Other identifiers: Not assessed
Category mappings: Not assessed
Brief: Not assessed
Revisions: 6 revisions. Latest: 21 October 2026.

Sources

Peer-reviewed study Developer

Munoz-Novoa M, Kristoffersen MB, Sunnerhagen KS, Naber A, Ortiz-Catalan M, Alt Murphy M (2025). Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study. Journal of NeuroEngineering and Rehabilitation 22:6.
Case report Developer

Kristoffersen MB, Munoz-Novoa M, Buist M, Emadeldin M, Reinholdt C, Ortiz-Catalan M (2024). Myoelectric motor execution and sensory training to treat chronic pain and paralysis in a replanted arm: a case study. Journal of NeuroEngineering and Rehabilitation 21:204.