Tissue site detection

A device includes a housing, an emitter, a detector, and a processor. The housing has a body contact surface. The emitter is coupled to the housing and has an emission surface and has an electrical terminal. The emission surface is configured to emit light proximate the body contact surface in response to a signal applied to the electrical terminal. The detector is coupled to the housing. The detector has a sense surface and an output terminal. The detector is configured to provide an output signal on the output terminal in response to light detected at the sensor surface. The processor is configured to implement an algorithm to determine a tissue site based on the emitted light and based on the detected light.

BACKGROUND

A variety of physiological parameters can be used to provide a measure of health for a patient. One such measurement is oxygen saturation (commonly referred to as SpO2) which relates to a measure of oxygenation of blood. Another example includes regional oxygen saturation (commonly referred to as rSO2) which relates to oxygenation of a region or tissue. Oxygenation can be determined using a system of optical emitters and optical detectors along with suitable processing.

Accurate measurement of oxygenation can be very important for health or safety. Accuracy of the oxygenation measurement is influenced by device calibration factors. Approaches to determining or selecting calibration factors have been inadequate.

OVERVIEW

The present inventors have recognized, among other things, that a problem to be solved can include determining calibration coefficients for accurate oxygenation measurement. The calibration coefficients are influenced by tissue characteristics or by the tissue site. The present subject matter can help provide a solution to this problem, such as by determining the site of the tissue.

Tissue characteristcs or tissue site information can be helpful for purposes in addition to selecting calibration coefficients for oxygenation measurement. For example, tissue site information can be useful for determining appropriate signal filters or for measuring motion of a particular site.

A device includes a housing, an emitter, a detector, and a processor. The housing has a body contact surface. The emitter is coupled to the housing and has an emission surface and has an electrical terminal. The emission surface is configured to emit light proximate the body contact surface in response to a signal applied to the electrical terminal. The detector is coupled to the housing. The detector has a sense surface and an output terminal. The detector is configured to provide an output signal on the output terminal in response to light detected at the sensor surface. The processor is configured to implement an algorithm to determine a tissue characteristic or site based on the emitted light and based on the detected light.

DETAILED DESCRIPTION

FIG. 1includes a view of system100having sensor10A, according to one example. Sensor10A includes a housing and is coupled to belt20. Belt20can be configured to encircle a portion of a body site and position sensor10A at a particular tissue site. Sensor10A includes a contact surface, and in the example shown, includes two emitters, here denoted as emitters30E, and includes four detectors, here denoted as detectors30D. Other arrangements and numbers of optical elements (emitters and detectors) are also contemplated.

Belt20can include other elements not shown in this figure, including an elastic element, an adjustor, a buckle or other fastener. Belt20can be fabricated of a textile product or other materials such as leather, fabric, or a polymer. Belt20can include a wrap or a bandage.

FIG. 2includes a side view of sensor10A and belt20, according to one example. In the figure, emitters30E can each include a single light emitting diode (LED) or include more than one LED. In addition, any particular LED can emit light having a single wavelength, multiple discrete wavelengths, or a spectrum of wavelengths. Emitters30E and detectors30D are located on a contact surface.

FIG. 3includes a view of sensor10B, according to one example. Sensor10B includes membrane25and includes emitters30E and detectors30D. Membrane25includes a planar material and has a contact surface28. Contact surface28, in one example, is configured as an adhesive surface for bonding to a tissue site. Membrane25can be rigid or flexible and can include a polymer material, a textile product, or other material. In one example, emitters30E and detectors30D are positioned within membrane25. In other examples, emitters30E and detectors30D are positioned below sensor10B and within an aperture of membrane25, and as such, can be described as having a position not within membrane25.

FIG. 4includes a view of user40fitted with a plurality of sensors, according to one example. Sensor10C is affixed at a tissue site at the chest of user40and in the example shown, is in the form of a patch and is coupled to the site by an adhesive. Sensor10D is affixed at a tissue site on a bicep of user40and sensor10E is affixed at a thigh of user40. Sensors10C,10D, and10E are attached using a belt or strap, however, in other examples, attachment mechanisms include adhesive, a clamp, and a garment (such as a sock, footwear, shirt, hat, scarf, or pants). The figure shows a user fitted with more than one sensor and in a particular instance, a user can be fitted with a single sensor or more than one sensor.

FIG. 5includes a block diagram of system50, according to one example. System50is configured for affixation to tissue at a site. System50is non-invasive and includes input/output module52, processor54, memory56, and optical emitter30E and optical detector30D.

Input/output module52can include a power switch, a mode control switch, a display, a user-control, a touch-screen, an indicator light, or other interface elements that enable a user to interact with system50. Input/output module52can include a wireless interface to allow communication with a remote device.

Processor54can include an analog processor. In one example, processor54includes a digital processor and is configured to execute instructions for implementing an algorithm. The instructions and data can be stored in memory56. Processor54can include an analog front end having an amplifier, a filter, a sample and hold circuit, an analog-to-digital converter (ADC), a digital-to-analog converter (DAC), an LED driver, or other modules.

Emitter30E can include a light emitting diode (LED) configured to emit light of a selected wavelength and power. Emitter30E can include a number of LED elements having different emitted light wavelengths. Detector30D can include a photodiode.

Light energy emitted by optical emitter30E can be directed to reflect or pass through tissue. Light detected by optical detector30D can be suitably processed to generate selected data in accordance with various examples of the present subject matter.

System50can be configured for wearing on a body. In this example, system50is powered by a portable power supply, such as a battery. System50can be affixed to a garment, a patch, or clamp device that remains in close proximity to the body for an extended duration.

FIG. 6includes a flow chart of method60, according to one example. Method60, at62, includes affixing a sensor to a tissue site. This can include bonding the sensor to the site using an adhesive. In various examples, this can include donning a garment, such as a shirt, or attaching the sensor using a belt or strap, or bandaging or wrapping a region of the body of the user.

At64, method60includes modulating an emitter, such as emitter30E, in accordance with an algorithm. The algorithm can be configured to determine a tissue site or configured to measure a physiological parameter. Operation of emitter30E can be controlled by a processor, such as processor54.

At66, method60includes detecting light using, for example, detector30D. A processor, such as processor54, can be configured to receive an output signal from a detector. The signal from the detector can correspond with the tissue site or can provide data for determining a physiological parameter of the tissue.

At68, method60includes determining a tissue characteristic or site using the emitted light and the detected light. This can include executing an algorithm, some examples of which are described elsewhere in this document. In one example, at68, method60includes determining an algorithm or determining a calibration based on a tissue characteristic or site.

According to one example, the sensor can be affixed using a wrap or a bandage. The sensor can be affixed at, for example, a bicep or a calf. A sensor can also be attached to a tissue site, such as a chest, using a patch or a foam pad. The patch or foam pad can have an adhesive surface.

In one example, a sensor is affixed to a tissue site using an attachment module having encoded information. The attachment module can be configured for affixation to a tissue site and configured to receive a sensor module. In one example, the sensor module can be readily removed and replaced without disturbing or altering the attachment module coupling to the tissue site. In one example, the sensor module can be removed and replaced after having separated the attachment module from the tissue site.

A sensor can be removed for servicing or battery recharging while the attachment module remains affixed to the tissue site. The attachment module is site-specific in that it includes encoded information tailored for a specific site. For example, an attachment module coupled to a belt of approximately 36 inches in length would be suitable for encircling a girth of a user. In a similar manner, an attachment module having relatively small profile contact surface may be tailored for attachment by adhesive to a site such as a chest area of a patient.

The sensor module is configured to read the encoded information associated with the attachment module. In addition, the sensor module is configured to apply calibration coefficients selected from a plurality of calibration coefficients based on the encoded information.

The information in the attachment module can be encoded using a component value (such as a resistance, a capacitance, an inductance, an impedance), using a combination of binary switches or storage registers, micro controller, or other manner of encoding. The sensor module can be configured to receive encoded information from the attachment module by an electrical connection, a reactive coupling (inductive or capacitive), or by an optical coupling.

The sensor may determine the body site and thereby select the appropriate calibration model and coefficients.

In one example, the sensor determines the tissue characteristic or site based on a classification criterion using a vector of quantitative features of an output signal. The output signal can be derived from a photodiode current, a pulse amplitude output or any signal derived from these measures, and, in the following description, is defined as x. Examples of a signal derived from these measures can include a photoplethysmography (sometimes referred to as PPG) waveform detrended with differencing n-times, subtracting a local regression, subtracting a signal mean, a derived value, using a low pass filtering, subtracting an exponential smoother, or normalizing to a scale.

The generalized square distance (Mahalanobis, Euclidean or other similar measure of distance) from each site can be calculated (e.g. (x−yt)TV−1(x−yt), where x is defined above as the vector of features, ytis a matrix of features for a given site, and V is a covariance matrix or function of the covariance matrix).

The sensor module placement is assigned to the site(s) with the posterior probability defined as p(s|x).

In other examples, machine learning techniques can classify varying influences under which the device is operating allowing customized algorithms and calibration methods. Such learning methods may include perceptron, logistic regression, decision trees, support vector machines, neural networks, principal component analysis, singular value decomposition, eigendecomposition, spectral theorem or Fisher's linear discriminant. Such examples, with the possible addition of kernel methods, can provide topological advantages for classification and computational simplification.

According to one example, a device includes a housing, an emitter, a detector, and a processor. The housing includes a body contact surface configured for affixation to a body at a particular tissue site. The emitter is coupled to the housing and has an emission surface and an electrical terminal. The emission surface is configured to emit light proximate the body contact surface in response to a signal applied to the electrical terminal. A detector is coupled to the housing. The detector has a sense surface and an output terminal. The detector is configured to provide an output signal on the output terminal in response to light detected at the sensor surface. The processor is configured to implement an algorithm to determine a tissue site based on the emitted light and based on the detected light.

The processor can be coupled to a memory and the memory can provide storage for instructions corresponding to the algorithm. In addition, the memory can provide storage for calibration coefficients. The memory can provide storage for a look-up table corresponding to tissue sites and calibration coefficients.

In one example, the algorithm is configured to select a calibration parameter based on the tissue characteristic or site. This can include evaluating an equation to determine coefficients based on a measured parameter associated with the tissue site. The tissue site can be determined, according to one example, based on a vector value. The algorithm can includes determining the tissue site based on an electric current or pulse amplitude at the output terminal. In one example, the algorithm determines a tissue site based on a calculated distance between an electric signal and a stored value.

In one example, the present subject matter is configured to determine an algorithm or determine a calibration based on a detected tissue site. As such, the system determines the location of the sensor and as a function of the location, determines an algorithm or calibration suitable for that site.

A system can include an attachment module and a sensor module. The attachment module can be configured for affixation at a selected tissue site. The attachment module can include a sensor receptor. The attachment module can include encoded information stored thereon. The encoded information is accessible to a communication interface coupled to the sensor receptor. The encoded information is determined by the tissue site.

The sensor module can be configured for placement in the sensor receptor. The sensor module can include a sensor element for determining a physiological parameter corresponding to the tissue site. The sensor element can include an optical detector. The sensor module is configured to couple with the communication interface of the attachment module. The sensor module is configured to access the encoded information and select at least one calibration coefficient corresponding to the encoded information.

The attachment module can include a wrap, an adhesively bonded pad, a belt, a clamp, or a garment. The encoded information can include a component value. The encoded information can include a resistance value, a conductance value, a capacitance value, an inductance value, or an impedance value. In one example, an optical parameter provides the encoded information. An optical parameter can include a modulated power level, a duty cycle, a frequency, a wavelength, or other parameter associated with the optics. The encoded information can include one or more switches or a micro controller.

The communication interface can include an electrical contact, a reactive coupling (such as an inductive coupling or a capacitive coupling) or an optical coupling including an emitter and a detector.

In one example, a system includes different sensors for each tissue site and each tissue site is configured with the calibration information for a particular site.

In one example, a user-operable switch (such as a switch or touch screen) is coupled to the sensor. The user-operable switch is configured to allow the user to select or specify the site location.

Various Notes & Examples