Modeling a neuronal controller exhibiting human postural sway

US11540781B2 · kind B2 · utility

Assignee

• Tata Consultancy Services Limited · IN

Inventors

• Aniruddha Sinha · Narayanpur, IN
• Oishee MAZUMDER · Sherghati, IN
• Debatri Chatterjee · Sherghati, IN
• Srinivasa Chakravarthy Vaddadi · Chennai, IN
• Dipayan Biswas · Chennai, IN

Key dates

• Filing date: Feb 25, 2020
• Grant date: Jan 3, 2023
• Expiry date: Jul 4, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H40/60
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Conventionally, a neuronal controller located inside the central nervous system governing the maintenance of the upright posture of the human body is designed from a control system perspective using proportional-integral-derivative (PID) controllers, wherein human postural sway is modeled either along a sagittal plan or along a frontal plane separately resulting in limited insights on intricacies of a governing neuronal controller. Also, existing neuronal controllers using a reinforcement learning (RL) paradigm are based on complex actor-critic on-policy algorithms. Analyzing human postural sway is critical to detect markers for progression of balance impairments. The present disclosure facilitates modelling the neuronal controller using a simplified RL algorithm, capable of producing postural sway characteristics in both sagittal and frontal plane together. The Q-learning technique of the RL paradigm is employed for learning an optimal state-action value (Q-value) function for a tuneable Markov Decision Process (MDP) model.