Neural and Muscle Control and Biomedical Signals

The main components of the human body from a control systems perspective

1. The control system: brain and spinal cord

2. Actuators: musculoskeletal system

3. Signal transmission: neurons

4. Sensors: vision, hearing, touch, etc.

Control System: Brain

Typically described by different regions, which correspond to different functions:

• The frontal lobe - located at the front and contains the motor cortex for controlling movement

• The parietal lobe - located at the top of the brain, involved in somatosensation and proprioception

• The occipital lobe - located at the back of the brain, involved in vision

• The temporal lobe - located at the base of the brain, involved in processing sounds

Control System: Spinal Cord

• The spinal cord is a thick bundle of nerve tissue that has a highly organised structure

• Transmits motor signals to muscles away from the brain (efferent)

  • Transmits sensory signals from the peripheral nervous system to the brain (afferent)

Signal Transmission: Neurons

Receive signals and transmit them around the body, made of three main components:

1. Dendrites, receive signals from other neurons

2. Axons, output signal to other neurons

3. Soma, cell body

The signals are known as action potentials - potential difference across the cell membrane created by movement of sodium ions

Actuators: Muscles

Three types of muscle:

1. Skeletal (voluntary) muscle

2. Smooth muscle

3. Cardiac (heart) muscle

Generate force by contracting, so are typically arranged in agonist/antagonist pairs.

Not single actuators, but composed of many muscle fibres, arranged in groups, each with a controlling motor neuron that forms a ‘motor unit’.

Sensors: Vision, Hearing, Touch

Sensory receptors convert a stimulus into an electrical signal in the nervous system.

The process of converting a physical/chemical stimulus to an electrical signal is called sensory transduction.

Types of Biomedical Signals

• Bioelectric

• Bioimpedance

• Bioacoustic

• Biomechanical

• Biochemical

• Bio-optical

Bioelectric definition

• A generic term for all of the electrical signals generated by nerve and muscle cells.

• The source is the membrane potential that, under certain circumstances, may generate an action potential.

• In single-cell measurements, the action potential is the bioelectric signal. However, in most cases an embedded or surface electrode measures the sum of the action potentials of a large number of cells.

• Biolectric signals include those from the brain (electroencephalogram, EEG), muscles (electromyogram, EMG) and heart (electrocardiogram, ECG).

Measurement of Bioelectric Signals

• The mechanism of electrical conductivity in the body involves ions as charge carriers.

  • Measuring bioelectric signals involves converting ionic currents into electric currents that will flow through wires.

  • This conversion process is carried out by electrodes that consist of electrical conductors in contact with the aqueous ionic (electrolyte) solutions in the body.

• Electrodes can be attached internally or to the body surface.

• Internal electrodes are typically needle electrodes made from stainless steel and can be single or arranged in arrays.

• Surface electrodes usually consist of a flat metal plate with a thin film of conductive electrolyte gel between the plate and the skin to establish contact

  • (‘dry’ electrodes also exist that rely on sweat to form the electrolyte layer but these tend to produce more noise).

  • Surface electrodes are commonly made of silver-silver chloride, which conduct well at both low and high frequency and produce few motion artefacts

Signal Acquisition

The raw measured signal passes through a number of signal processing steps:

1. Signal conditioning - amplification by analogue electronic circuits

2. Low-pass anti-aliasing filter - must be low-pass filtered at or below Nyquist frequency before sampling to avoid alaising

3. Analogue to digital conversion - sampling at discrete time steps at a specific sampling frequency and quantisation

4. Digital signal filtering - specific frequency region is passed by the filter and the rest removed from the signal

Filter Design Examples

1. Butterworth - maximum in-band flatness but slow roll off

2. Chebyshev type 1 - fast roll off but in-band ripple

3. Chebyshev type 2 - fast roll off but out-band ripple

4. Elliptic - steep roll off but in/out band ripple

Filter Design Specifications

1. Filter type (low-pass, high-pass, band-pass, band-stop)

2. Filter design

3. Cut-off frequency or range of band-pass/band-stop frequencies

4. Filter order (higher order gives steeper roll-off but more computationally complex)

Robust Filter Design

High order filters tend to be unstable if implemented directly as a high order difference equation.

Instead, filters are usually implemented as a cascade of low order filters.

A cascade of second order filters is known as a biquad design, or second order sequence (SOS)