EP4687644A1 - Body-worn sensor with haptic interface - Google Patents

Abstract

A sensor worn entirely on a patient's body includes a microphone sensor, a haptic interface, and a processing system. The microphone sensor measures acoustic signals generated by the patient's body. The haptic interface is configured to generate a haptic response. The processing system is programmed to receive the acoustic signals from the microphone sensor and execute computer code that: process the acoustic signals to detect swallowing, respiration, coughing, or a combination thereof; and control the haptic interface to generate the haptic response responsive to processing the acoustic signals.

Description

PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 BODY-WORN SENSOR WITH HAPTIC INTERFACE Inventors: Ha Uk Matt Keller Keum San Chun Assignee: Sibel Health Inc. N. Alexander Nolte Nolte Lackenbach Siegel 30798 Kingsland Blvd., BLDG B STE 200 Brookshire, TX 77423 Attorney Docket No.: SIBEL-006PCT PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 BODY-WORN SENSOR WITH HAPTIC INTERFACE CROSS REFERENCE TO RELATED APPLICATION [0001] The priority to and benefit of co-pending U.S. Patent Application Serial No. 63/494,108, filed April 4, 2023, the entire contents of which are hereby incorporated by reference as if fully set forth herein. TECHNICAL FIELD [0002] This disclosure relates generally to systems for monitoring and providing care to patients, e.g., those suffering from Parkinson’s disease, in both in the hospital and at home. BACKGROUND [0003] This section of this document introduces information about and/or from the art that may provide context for or be related to the subject matter described herein and/or claimed below. It provides background information to facilitate a better understanding of the various aspects of the present disclosure. This is a discussion of “related” art. That such art is related in no way implies that it is also “prior” art. The related art may or may not be prior art. The discussion in this section of this document is to be read in this light, and not as admissions of prior art. [0004] Swallowing, a primary function of human survival, is a highly complex synergy of rapid and interdependent movements triggered through sensory end organs in the oral cavity, pharynx, and larynx. This action not only serves to protect the airway from aspiration but also propels ingested material (herein “bolus”) throughout the upper aerodigestive tract (see, for example, Logemann et al., Evaluation and treatment. Folia PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 Phoniatr Logop.1995;47(3):140-64). The significance of swallowing function is amplified by the millions of adults who suffer from swallowing problems (herein “dysphagia”) related to neurologic conditions, head and neck cancer, gastrointestinal and respiratory diseases. [0005] Diseases and conditions that impair the physiological mechanisms that control swallowing or directly insult peripheral structures involved in swallowing movements can result in dysphagia ranging from problems that range from mild to life-altering problems, and present significant rehabilitation challenges (see, for example, Shaw et al., The normal swallow: muscular and neurophysiological control. Otolaryngol Clin North Am. 2013;46(6):937-56). Dysphagia may involve altered sensation that delays the onset of swallowing movements, reductions in muscle strength, and range and coordination of the timing of movements (see, for example, Martin-Harris et al., Breathing and swallowing dynamics across the adult lifespan. Arch Otolaryngol Head Neck Surg. 2005;131(9):762-70). Adding to the complexity of the control and execution of swallowing, breathing must be intimately timed with swallowing initiation because the pharyngeal cavity, common to both functions, interchanges between patency during breathing to facilitate effortless movement of air to tight compression during swallowing, generating high positive pressures on the bolus required for clearance through the upper aerodigestive tract. [0006] Patients with conditions that impact their swallowing include those suffering from Parkinson’s disease, head and neck cancer, Alzheimer’s disease and other forms of dementia, Myasthenia Gravis, amyotrophic lateral sclerosis (herein “ALS”), and related diseases. Moreover, in addition to their impact on swallowing, these conditions can impact the patient’s speech (e.g. by causing them to slur their speech or speak lightly and levels not perceptible by others), initiate drooling, etc.). [0007] Respiratory-swallowing coordination is critical for safely and efficiently transporting foods and liquids from the mouth into the esophagus. In healthy adults, the timing of swallow initiation typically corresponds with a pause in the expiratory phase of quiet breathing at mid-to-low lung volumes. This coordinative pattern is: 1) vital for airway protection; 2) facilitates physiological events beneficial to swallowing safety and PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 efficiency, such as tongue base retraction, laryngeal elevation, and pharyngoesophageal segment opening; and 3) subsequently aids in bolus clearance (see, for example, Hopkins-Rossabi et al. Respiratory-swallow coordination and swallowing impairment in head and neck cancer. Head Neck-J Sci Spec. 2021;43(5):1398-408). However, it is well-documented that the coordination of breathing with swallowing is significantly disrupted in patients with dysphagia, resulting in impairments in the swallowing mechanism and significant decreases in health and quality of life. Traditional swallowing interventions typically use a single-system approach, focusing on increasing the strength and range of motion of pharyngeal structures. [0008] Despite demonstrated positive outcomes of these approaches, most patients continue living with swallowing impairments. More recently, a novel intervention that trains patients with dysphagia to initiate swallowing during the expiratory phase of the breathing cycle has shown to decrease aspiration and improve swallowing biomechanics in some patient populations (see, for example, Martin-Harris et al., Respiratory-Swallow Training in Patients With Head and Neck Cancer. Arch Phys Med Rehab. 2015;96(5):885-93.). However, three significant methodologic challenges exist in the rehabilitation of swallowing function: 1) the ability to unambiguously detect the occurrence of swallowing and swallowing coordinated with breathing without the use of expensive, non-portable imaging and respiratory recording equipment; 2) the ability to ensure the fidelity of the swallowing intervention and provide visual cueing to enhance performance in real-time, and 3) the ability to facilitate stability of the acquired swallowing skills through ambulatory monitoring and cueing. [0009] Currently, devices that measure swallowing are used mostly in research settings. The current gold-standard methodologies for such devices includes two techniques: 1) Respiratory inductance plethysmography (herein “RIP”) methods that measure the overall expansion of a patient’s ribcage and abdomen via inductance coils; and 2) nasal cannulas that monitor pressure differentials at the nasal cavity as an absolute measurement of nasal airflow. Devices that capture synchronous nasal airflow PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 and kinematics of the ribcage and abdomen can make accurate assessments of respiratory-swallow phase patterning.

PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 SUMMARY [0010] In view of the foregoing, it would be beneficial to have a body-worn sensor that is optimized for monitoring swallowing events (herein “SW”) and their timing relative to a patient’s respiratory phases (i.e., inspiration, expiration). Even more beneficial would be a sensor that stimulates the patient with, e.g., a vibratory response (herein a “haptic interface”) that warns the patient of an SW occurring at an incorrect time, with the ultimate goal of training the patient to swallow at a correct time. In addition, patients with swallowing problems naturally have less swallow events. Thus, another beneficial use of the technique disclosed herein includes increasing the patient’s swallowing events with a haptic interface, e.g. a vibratory reminder. And yet another advantage is the haptic interface, when timed properly, can reduce the patient’s degree of drooling and even cause them to speak louder. [0011] In a first aspect, a sensor worn entirely on a patient’s body comprises a microphone sensor, a haptic interface, and a processing system. The microphone sensor is configured to measure acoustic signals generated by the patient’s body. The haptic interface is configured to generate a haptic response. The processing system programmed to receive the acoustic signals from the microphone sensor and execute computer code that: processes the measured acoustic signals to detect swallowing, respiration, coughing or a combination thereof; and controls the haptic interface to generate the haptic response responsive to the processing of the measured acoustic signals. [0012] In a second aspect, a method for assisting a patient with swallowing, comprises: measuring a plurality of acoustic signals generated by the patient’s body; processing the measured acoustic signals to detect swallowing, respiration, coughing, or a combination thereof, of the patient; and controlling the haptic interface to generate a haptic response responsive to the processing of the measure acoustic signals. [0013] In a third aspect, a wearable sensor comprises a first physiological sensor, a haptic interface, and a processing system. The first physiological sensor is configured to PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 acquire a first set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase. The haptic interface is configured to generate a haptic response. The processing system is programmed to receive the motion signals from the motion sensor and to: process the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; and control the haptic interface to generate the haptic response by collectively processing the first and second signals and a pre-determined parameter indicating an opportunity for the patient to swallow. [0014] In a fourth aspect, a computer-implemented method comprises: receiving a first set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase from a first physiological sensor, the first physiological sensor positioned on the patient’s suprasternal notch; processing the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; processing the first and second signals and a pre-determined parameter indicating an opportunity for the patient to swallow; and generating a haptic response through a haptic interface, the haptic response to prompt the patient to swallow. [0015] In a fifth aspect, a system comprises a wearable system, an external gateway, and a computing system. The wearable sensor is configured to: acquire a first set of physiological signals from a patient, the first set of physiological signals being potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase; process the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; and generate a haptic response indicating an opportunity for the patient to swallow. The external gateway is programmed to wirelessly receive information transmitted from the wearable sensor. The computing system in which the transmitted information may be stored or through which the transmitted information may be accessed. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [0016] The above presents a simplified summary of the subject matter claimed below in order to provide a basic understanding of some aspects of the invention. This summary is not an exhaustive overview of the claimed subject matter. Nor is it not intended to identify key or critical elements of the invention or to delineate the scope of protection. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is discussed later. BRIEF DESCRIPTION OF THE DRAWINGS [0017] In the drawings, like reference numbers generally indicate identical, functionally similar, and/or structurally similar elements. [0018] Fig.1 is a photograph of a patient wearing the body-worn sensor according to one or more embodiments featuring a motion-detecting accelerometer and a haptic interface; [0019] Fig.2A and Fig.2B are an assembled view and an exploded mechanical view, respectively, of the body-worn sensor of Fig.1; [0020] Fig.2C is a schematic block diagram of the electronics of the body-worn sensor of Fig.1; [0021] Fig.3A is a graph of time-dependent motion signals measured along the x, y, and z-axes of an accelerometer within the body-worn sensor of Fig.1; [0022] Fig.3B is a graph of time-dependent energy signals calculated from the time- dependent motion signals of Fig.3A; [0023] Fig.4A is a graph of processed acceleration signals from the x, y, and z-axis of an accelerometer and respiration signal derived from the z-axis acceleration signal; [0024] Fig.4B is a diagram showing the signal processing steps and the convolutional neural network (CNN) architecture used for detecting SWs; PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [0025] Fig.5 is a graph showing a theoretical time-dependent respiratory tidal volume measured from a patient, with a time period indicating ‘safe swallow interval’ superimposed on the graph; [0026] Fig. 6A is a graph of a respiratory signal generated from a time-dependent motion signal measured along the z-axis with the accelerometer within the body-worn sensor of Fig.1; [0027] Fig.6B is a graph of a time-dependent motion signal used for Fig.6A with the respiratory component of the signal filtered out to show a SW; [0028] Fig. 7 is a flow chart of an algorithm used to detect an SW and, in response, generate haptic feedback to the patient based on the timing of the SW; [0029] Fig.8 is a schematic drawing of a patient wearing the body-worn device of Fig. 1 that measures an SW and is triggered by an external device to generate a haptic response; [0030] Fig.9A is a graph of a time-dependent motion signal measured along the z-axis with the accelerometer within the body-worn sensor of Fig.1; [0031] Fig.9B is a graph of a time-dependent respiratory signal determined by filtering the time-dependent motion signal of Fig.9A; [0032] Fig. 10A is a graph of a time-dependent motion signal measured along the z- axis with the accelerometer within the body-worn sensor of Fig.1; [0033] Fig. 10B is a graph of a time-dependent cardiac signal determined by filtering the time-dependent motion signal of Fig.10A; [0034] Fig. 11A is a graph of a time-dependent motion signal featuring respiratory signal and SW occurring in four different ‘Cases’, each corresponding to a different phase between the respiratory signal and SW; [0035] Fig.11B is a graph of a time-dependent haptic signal delivered because of the SWs shown in Fig.11A; PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [0036] Fig. 12 is a graph showing the average number of swallows per minute measured from a cohort of patients with Parkinson’s disease with and without haptic feedback provided by the body-worn sensor of Fig.1; [0037] Fig. 13 is an alternate configuration of the sensor of Fig. 1 featuring a first portion containing sensing elements for measuring HR and RR, a third portion containing an accelerometer for measuring SWs, and a second portion connecting the first and third portions; [0038] Fig. 13A and 13B are photographs of the sensor of Fig. 13 wherein the first portion is positioned, respectively, on the patient’s suprasternal notch and chest, and the third portion is positioned, respectively, on the patient’s larynx and SN; [0039] Fig.14 is a photograph of a patient wearing both a patch sensor on their chest and an oximeter sensor on their finger, with both sensors including physiological sensors and a haptic interface; and [0040] Fig. 15A-C show the body-worn sensor of Fig. 1 worn, respectively, on a patient’s SN, hand, and arm; [0041] While the disclosed subject matter is susceptible to various modifications and alternative forms, the drawings illustrate specific implementations described in detail by way of example. It should be understood, however, that the description herein of specific examples is not intended to limit that which is claimed to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the appended claims. DETAILED DESCRIPTION [0042] Illustrative examples of the subject matter claimed below are disclosed. In the interest of clarity, not all features of an actual implementation are described for every example in this specification. It will be appreciated that in the development of any such actual implementation, numerous implementation-specific decisions may be made to PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 achieve the developers’ specific goals, such as compliance with system-related and business-related constraints, which will vary from one implementation to another. Moreover, it will be appreciated that such a development effort, even if complex and time-consuming, would be a routine undertaking for those of ordinary skill in the art having the benefit of this disclosure. [0043] A body-worn sensor according to one embodiment monitors a patient’s SWs time-dependent phase relative to expiration; the sensor includes a haptic interface that alerts the patient to the ideal time for an SW. Such a sensor addresses the rehabilitation needs of millions of adults who suffer from dysphagia related to neurologic conditions, head and neck cancer, and gastrointestinal and respiratory diseases. The body-worn sensor according to some embodiments, when worn near the throat, simultaneously measures SWs and movements in the patient’s upper chest related to respiratory actions (e.g. breathing). For most patients, an ideal location for the body-worn sensor is the suprasternal notch (herein “SN”), or, less ideally, the sternal manubrium (herein “SM”). In patients whose SWs induce only small amplitude motions of the throat, the sensor can be located above the SN, up to and including locations coincident with the laryngeal prominence (herein “LP”), to increase the magnitude of the signal. The sensor also measures vital signs from the patient, e.g. heart rate (herein “HR”) and respiration rate (herein “RR”), along with signals related to the patient’s physical activity, posture, and body position. [0044] Given the above, in one aspect, a body-worn sensor may be worn entirely on a patient’s body and without any functional components that are not worn on the body. The body-worn sensor features: 1) a motion sensor that measures time-dependent motion signals modulated by the patient’s swallowing and respiration; 2) a haptic interface that generates a haptic response; and 3) a processing system that receives the motion signals from the motion sensor and executes computer code that: i) processes the motion signals to determine a first signal related to a presence or absence of a SW, and a second signal related to the patient’s respiration; and ii) controls the haptic interface to generate the haptic response by collectively processing PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 the first and second signals and a pre-determined parameter indicating an ideal temporal point for the patient to swallow. [0045] In some embodiments, the body-worn sensor is worn entirely on the patient’s SN. In other embodiments, the second signal is a time-dependent one indicating the patient’s inspiration and expiration. Here, the predetermined parameter indicates a temporal period when the patient should be expiring, and the processing system generates the haptic response when it determines that the SW does not occur when the patient is expiring. [0046] In related embodiments, the predetermined parameter indicates a temporal period when the patient should be inspiring, and the processing system generates the haptic response when it determines that the SW occurs when the patient is inspiring. Or the predetermined parameter can indicate a temporal period between when the patient is inspiring and expiring, and the processing system generates the haptic response when it determines that the SW occurs between when the patient is inspiring and expiring. [0047] In other embodiments, the second signal is a time-dependent signal indicating the patient’s respiratory tidal volume. Here, for example, the predetermined parameter indicates a temporal period when the patient’s respiratory tidal volume is around 25% of its maximum, and the processing system generates the haptic response when it determines that the SW occurs when the tidal volume is greater than 25% of its maximum. [0048] In other embodiments, the motion sensor is an accelerometer. The accelerometer is typically configured to measure time-dependent motion signals along x, y, and z-axes corresponding to the patient, and the processing system is programmed to process at least one time-dependent motion signal with a first algorithm to determine a time-dependent ‘energy’ signal. In related embodiments, the first algorithm is programmed to collectively process time-dependent motion signals measured by the accelerometer along the x, y, and z-axes to determine the time- dependent energy signal, which can, for example, be defined by the following equation: PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 ^^( ^^) ~ √ ^^( ^^)² + ^^( ^^)² + ^^( ^^)² [0049] where E(t) is the , y(t), and z(t) are the time- dependent motion signals along, respectively, the x, y, and z-axes corresponding to the patient. [0050] In other embodiments, the processing system is further programmed to process the time-dependent energy signal with a second algorithm programmed to count features in the time-dependent energy signal, with each feature corresponding to a swallowing event. The second algorithm, for example, identifies peaks in the time- dependent energy signal induced by SWs associated with the patient. More specifically, the second algorithm can identify features in the peaks or a mathematical derivative of the peaks comprising at least one of the following: i) peak maximum; ii) peak foot; iii) peak width; iv) the inflection point at which the feature changes from a positive to negative value; and v) area underneath the peak. [0051] In other embodiments, the processing system is programmed to process the time- and frequency-dependent signals with a third algorithm programmed to extract features from the time- and frequency-dependent signals, with each feature corresponding to a SW. The third algorithm collectively uses x-, y-, and z-axis acceleration signals as well as a respiration signal deduced from the z-axis acceleration to capture relevant characteristics associated with the SWs. More specifically, the third algorithm computes features by convoluting each time- and frequency-dependent signals from the x-, y-, and z-axis acceleration. [0052] In other embodiments, the haptic interface can be a vibratory motor, a mechanical buzzer, a device that delivers an electric current to the patient, a light- emitting diode, a piezoelectric device, and/or a device that emits an acoustic sound. [0053] In another aspect, some embodiments provide a body-worn sensor that includes: 1) a motion sensor (e.g. an accelerometer or gyroscope) that measures time- dependent motion signals modulated by the patient’s swallowing; 2) a respiration sensor comprising a pair of electrodes that measure a time-dependent electrical signal modulated by the patient’s respiration; 3) a haptic interface that generates a haptic PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 response; and 4) a processing system that receives the motion signals from the motion sensor and the time-dependent electrical signal from the respiration sensor, and executes computer code that: i) processes the motion signals to determine a first signal related to a presence or absence of a SW; ii) processes the electrical signals to determine a second signal related to the patient’s respiration; and iii) controls the haptic interface to generate the haptic response by collectively processing the first and second signals and a pre-determined parameter indicating an ideal temporal point for the patient to swallow. [0054] In embodiments, the respiration sensor is an electrocardiogram (herein “ECG”) sensor, and the time-dependent electrical signal is an ECG waveform. Here, the processor is further programmed to analyze the envelope of the ECG waveform to determine the second signal related to the patient’s respiration. [0055] In embodiments, the impedance sensor includes at least two sense electrodes and at least two drive electrodes. Here, the two sense electrodes measure a voltage related to electrical current injected by the two drive electrodes and impedance changes induced by the patient’s respiration. [0056] In yet another aspect, embodiments provide a sensor worn entirely on a patient’s body that includes a microphone sensor configured to measure acoustic signals modulated by the patient’s speech volume. The sensor also includes a haptic interface that generates a haptic response, and a processing system programmed to receive the acoustic signals from the microphone sensor and execute computer code that: i) processes the acoustic signals to determine a first signal related to a volume of the patient’s speech; and ii) control the haptic interface to generate the haptic response by collectively processing the acoustic signals and a pre-determined parameter indicating an ideal volume of the patient’s speech. [0057] In embodiments, the processing system is further programmed to process an amplitude of the acoustic signals, or is programmed to determine a frequency profile of the acoustic signals. For example, the processing system can determine an amplitude of a select frequency component within the frequency profile. In other embodiments, the processing system can generate the haptic response when the amplitude of the PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 acoustic signal, or the amplitude of the select frequency component, is less than the pre-determined parameter. [0058] In embodiments, the select frequency component is between 20 Hz and 20,000 Hz. In other embodiments, the microphone sensor is a digital microphone or an analog microphone. In still other embodiments, the microphone sensor is an accelerometer. [0059] Referring to Fig.1, a body-worn sensor 10 that measures SWs and features a haptic interface attaches to the SN 12 of a patient 14 to measure swallowing, along with physiological signals related to the patient’s RR, HR, and respiratory tidal volumes. More specifically, during use, the sensor 10 detects SWs and—perhaps more importantly in the case of patients suffering from Parkinson’s disease—the lack of swallowing. As described in more detail below, ideally as SW is coordinated, i.e. ‘is in phase with’, the patient’s respiratory response, with it preferably occurring after inspiration is completed and during a period of mid-to-low lung volume. This period is referred to below as the ‘safe swallow interval.’ When the lack of a properly timed SW (or no SW) is detected, the sensor initiates a haptic signal, such as a vibratory signal (e.g. a ‘buzz’) that stimulates the patient’s SN 12. This reminds the patient to swallow. Over time, this action by the sensor may ‘train’ the patient to swallow at appropriate times. It can also count SWs, and use these for analytical and/or clinical purposes. [0060] In general, it is contemplated by the present disclosure that sensor 10 includes physiological sensors, electronic components and/or electronic computing devices operable to receive, transmit, process, store, and/or manage patient data and information associated performing the functions of the system as described herein. This contemplation encompasses any suitable processing device adapted to perform computing tasks consistent with the execution of computer-readable instructions stored in a memory or a computer-readable recording medium. To further an understanding of the claimed subject matter and how this contemplation may be manifested, one particular example of the sensor 10 will now be discussed. [0061] Fig. 2A and FIG. 2B show the sensor 10 in more detail. An outer housing 20 composed of a soft, stretchable polymeric material (e.g. a silicone elastomer, such as Silbione®) encloses a printed circuit board (herein “PCB”) 21, which serves as an PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 electronic module for the sensor 10. The outer housing 20 attaches to a housing base 40, also typically composed of a silicone elastomer that adheres to the outer housing 20 to form a water-tight seal. To couple the sensor 10 to the patient, a thin adhesive layer (not shown in the figure) is stuck to the housing base 40, and then applied to the patient’s SN with a light pressure to adhere it thereto. [0062] The PCB 21 typically features a combination of rigid and flexible circuits that mount a physiological sensor, such as a first accelerometer 32, positioned on an outwardly facing portion of the PCB 21 that connects to a base portion 26 through a first thin, flexible arm 28 that includes conductive traces. The flexible arm 28 typically features a serpentine-type pattern that allows it to stretch while maintaining electrical conductivity. The conductive traces are in electrical contact with underlying conductive pads in the first accelerometer 32 that allow it to be controlled by circuitry within the PCB 21, as described below. A second accelerometer 22 mounts on a small fiberglass circuit board 25 that connects to the base portion 26 through a second thin, flexible arm 23 that also includes conductive traces and features a serpentine-type pattern. Both the first 32 and second 22 accelerometers measure time-dependent signals along x, y, and z-axes; these are modified by physiological events, such as respiratory and cardiac responses (yielding, respectively, values of RR and HR), as well as by SNs and general motion of the patient. [0063] Also mounted on the base portion 26 is a power-management integrated circuit (herein “PMIC”; not shown in Fig.2A-Fig.2B), i.e., a chip that takes a voltage input from a rechargeable Li-ion battery 30 and converts it into appropriate voltages that drive the various PCB-mounted components. A low-power Bluetooth® transceiver (also not shown in Fig. 2A-Fig. 2B) mounts to the base portion 26 and wirelessly transmits processed data and signals from the sensor 10 to an external gateway, as shown in more detail in Fig. 8. In addition to the Bluetooth® transceiver is an embedded microprocessor that operates to control the sensor 10 to, among other things, process time-dependent waveforms measured by the first 32 and second 22 accelerometers to determine signals related to RR, HR, SNs, and general motion, and in response generate a haptic interface. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [0064] A haptic motor 24 connects to the fiberglass circuit board 25. When activated, the haptic motor 24 generates the haptic interface described above. The haptic motor 24 can take several forms, all of which exhibit vibratory action (i.e. ‘buzzing’) when activated. One form is an ‘eccentric rotating mass’ component that, when driven with a time-dependent analog or digital signal controlled by the embedded microprocessor, causes the haptic motor to rotate in a specific direction to cause a vibration that is then felt by the patient. A second form is a ‘linear resonant actuator’ that typically features a hockey puck-type shape, and vibrates in a similar manner in response to the analog or digital signal. A third type is a ‘piezoelectric module’ that rapidly expands and contracts in response to the driving signal (typically a time-dependent analog voltage), thereby causing it to vibrate. Other types of haptic motors or actuators, particularly those that can be easily mounted to the PCB 21, can also be used for this application. [0065] As described above, a rechargeable Li-ion battery 30 powers the PCB 21. An inductive coil (not shown in Fig.1) imprinted onto the PCB 21 may charge the battery 30 when it is exposed to an electromagnetic field. Alternatively, the PCB 21 may include a port, such as a USB port, that connects to a power source to recharge the battery 30. [0066] The first 32 and second 22 accelerometers each measure time-dependent signals along their x, y, and z-axes. During this process, the microprocessor within the Bluetooth® transceiver processes these motion-driven signals to determine the respiratory, cardiac, and SNs, as described above. Such processing, for example, may involve applying algorithms to the signals, such as calculating a mathematical difference between the signals; this technique may remove baseline components to better isolate certain signals (e.g. those related to subtle SNs) that are otherwise too weak to accurately measure. Alternatively, the microprocessor may determine the ‘energy’ of the signal by determine its overall signal magnitude; this is typically done by squaring each of the signals, adding them together, and then taking a square root. Typically, the most significant signal measured by either accelerometer is that corresponding to an axis that points directly into the patient’s chest or SN; most often, this is either the y or z-axis. [0067] As shown in FIG.4A, the electronics 33 of the body-worn sensor 10 may, for example, include a sensor interface 34, one or more processors 35, a communications PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 interface 36, a memory 37, and a power source (or power connection) 38. Communications are conducted over an internal bus 39. The sensor interface 34 may be implemented in hardware or combination of hardware and software and is used to connect via wired connections 33a to the physiological sensors for gathering data from the patient 14. The data signals from the physiological sensors may include, for example, sensor data related to the respective physiological data the physiological sensors are designed and deployed to collect. [0068] The one or more processors 35 may be used for controlling the general operations of the body-worn sensor 10, as well as processing sensor data received by sensor interface 34, as described herein. The one or more processors 35 may be any suitable processor-based resource known to the art. They may be, but are not limited to, a central processing unit (“CPU”), a hardware microprocessor, a multi-core processor, a single core processor, a field programmable gate array (“FPGA”), a controller, a microcontroller, an application specific integrated circuit (“ASIC”), a digital signal processor (“DSP”), or other similar processing device capable of executing any type of instructions, algorithms, or software for controlling the operation and performing the functions of body-worn sensor 10. In some embodiments, the one or more processors 35 may comprise a processor chipset including, for example and without limitation, one or more co-processors. [0069] The communications interface 36 may permit the body-worn sensor 10 to directly or indirectly communicate with one or more computing networks and devices, workstations, consoles, computers, monitoring equipment, alert systems, and/or mobile devices (e.g., a mobile phone, tablet, or other hand-held display device). The communications interface 36 may include various interfaces, communication channels, cloud, antennas, and/or circuitry to permit wireless communications with such computing networks and devices. In essence, any wireless communication protocol may be used. [0070] The memory 37 may be a single memory device or one or more memory devices at one or more memory locations that may include, without limitation, one or more of a random-access memory (“RAM”), a memory buffer, a hard drive, a database, PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 an erasable programmable read only memory (“EPROM”), an electrically erasable programmable read only memory (“EEPROM”), a read only memory (“ROM”), a flash memory, hard disk, various layers of memory hierarchy, or any other non-transitory computer readable medium. The memory 37 may be on-chip or off-chip depending on the implementation of the one or more processors 35. The memory 37 may be used to store any type of instructions and patient data associated with algorithms, processes, or operations for controlling the general functions and operations of the body-worn sensor 10. [0071] The power source 38 may include a self-contained power source such as a battery pack and/or include an interface to be powered through an electrical outlet, either directly or by way of a monitor mount. The power source 38 may also be a rechargeable battery that can be detached allowing for replacement. In the case of a rechargeable battery, a small built-in back-up battery (or super capacitor) can be provided for continuous power to be provided to the body-worn sensor 10 during battery replacement. Communication between the components of the body-worn sensor 10 in this example may be established using the internal bus 39. [0072] The data signals received from the physiological sensors may be analog signals. For example, the data signals may be input to the sensor interface 34. The sensor interface may include amplifying and filtering circuity as well as analog-to-digital (“A/D”) circuity that converts the analog signal to a digital signal using amplification, filtering, and A/D conversion methods. Thus, the sensor interface 34 is a component which may be configured to interface with the one or more physiological sensors and receive sensor data therefrom. [0073] As further described herein, the processing performed by a data acquisition circuit (not separately shown) within the sensor interface 34 may generate analog data waveforms or digital data waveforms that are analyzed or processed by, in this particular embodiment, one of more processors 35. However, other embodiments may use other kinds of processors disclosed above. The one or more processors 35, for example, may analyze the acquired data as described herein below. Thus, the one or PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 more processors 35 furthermore execute various computer-implemented methods attributable to the body-worn sensor 10 in accordance with the present disclosure. [0074] Figs. 3A and 3B show examples of time-dependent waveforms measured by the accelerometers as described above. Different SWs—i.e. those involving just saliva as shown by the bracket 50, those involving swallowing fluid from a cup shown by the bracket 52, and those involving swallowing fluid with a straw shown by the bracket 54— modulate the waveforms in different ways. Fig. 3A shows waveforms measured along individual axes of the accelerometer during these SWs. As is clear from these data, the act of swallowing modulates the waveforms, with the most pronounced modulation being along the y-axis. [0075] Fig.3B shows a single, processed waveform representing the energy of motion detected from the patient’s suprasternal notch. The energy is calculated as described above, i.e. by squaring the signal measured along each axis, adding them together, and then taking the square root of the sum. As is clear from this singular waveform, the time- dependent energy shows a series of sharp peaks, each representing an SW marked by an inverted triangle. Swallow events are detected under three different conditions, indicated by brackets 50, 52, and 54, and described above. [0076] Fig.4A shows an example of processed, time-dependent waveforms measured by the accelerometers as described above. A SW modulates the waveforms in different ways. As is clear from the data, the act of swallowing modulates the waveforms, with the most pronounced modulation being along the y-axis acceleration and the respiration. [0077] Fig. 4B shows the signal processing steps and machine learning architecture employed for detecting SWs. In this architecture, the motion signals are sequentially processed via three steps: signal processing, feature extraction, and classification. The signal processing step prepares the motion signals for feature extraction. This step consists of three parts: baseline removal, band pass filtering, and Fast Fourier Transform (FFT). In the baseline removal, a baseline is extracted using a technique called moving average. This baseline is subsequently removed from the original segment. Then, the resulting signal is passed through a band pass filter (BPF). After PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 BPF, the filtered signal is duplicated, and one of the copies is used for FFT computation and the other is directly appended to the computed FFT. The processed time- dependent waveforms from Fig.4A are input to the convolutional neural network (CNN) architecture for feature extraction and model training. For feature extraction, two stacked 1-D convolutional layers are used. Each convolutional layer is followed by a batch normalization layer. Features are extracted through the convolutional layers, and are passed through a flatten layer and two fully connected (dense) layers for classification. As the final output from the classification stage, the probability of swallow is provided for the given segment. [0078] Healthy adults typically initiate swallows during the expiratory phase of the breathing cycle at mid-to-low lung volumes. The respiratory phase in which swallowing is initiated influences the biomechanics necessary for airway protection and efficient clearance of food and liquids through the pharynx. As a result, monitoring respiratory- swallow coordination—i.e. the phase of these components—and then training to initiate SWs during the expiratory phase of breathing in patients with dysphagia can lead to improved airway protection and pharyngeal clearance. [0079] Given that, Fig. 5 shows a time-dependent plot indicating an ideal swallowing pattern for a healthy subject. Fig.5 plots respiratory tidal volume vs. time, with the peak of the plot (i.e. the peak respiratory tidal volume) indicating the inspiration/expiration transition. Respiratory tidal volume can be estimated by amplitudes of the accelerometer-measured respiratory signal. As the subject begins expiration, tidal volume decreases in a systematic manner until it reaches a minimum when lung volume is at its lowest. During this period of mid-to-low expiration, and as described above, the subject’s airway is then theoretically cleared of any food and liquids, indicating a ‘safe swallow interval’, and indicated by the shaded box 95 in the figure. [0080] Figs. 6A and 6B show, respectively, time-dependent waveforms indicating a respiratory signal and an SW, as determined from a motion signal measured with a sensor similar to that shown in Fig.1. The motion signals are processed with different bandpass filters, described in more detail below, to yield the time-dependent respiratory signal shown in Fig. 6A, and the SW shown in Fig. 6B. The bandpass filters are PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 implemented using embedded computer code running on the microprocessor within the sensor; alternatively, this type of ‘digital signal processing’ can be performed off-line, e.g. using an external gateway described in more detail below, such as a mobile phone or tablet computer. The respiratory signal includes low-frequency pulses that correspond to each breath made by the patient, with each low-frequency pulse including an upwardly rising slope indicating inspiration, as indicated by the dashed line 100, and a downwardly falling slope indicating expiration, as indicated by the dashed line 102. Gray boxes 103a,b in the figures highlight the expiratory cycle. [0081] The time-dependent waveform shown in Fig. 6B originates from the same motion signal used to generate the respiration signal in Fig.6A, only it has been filtered with a bandpass filter chosen to remove the relatively low-frequency respiration pulses shown in Fig. 6A, leaving signals corresponding to a relatively high-frequency SW, as shown in Fig. 6B and indicated by the dashed line 104. This SW is caused by movement of fluid in the patient’s SN, and features a high-frequency pulse that is modulated up and down in a manner commensurate with rapid movements of the SN. [0082] The waveforms shown in Figs.6A and 6B are measured from a healthy subject. It indicates how such a patient, because of their autonomic nervous system, intrinsically swallows during the safe swallow interval. However, patients suffering from Parkinson’s disease—a progressive disease of the central nervous system—often lack such a capability. The currently disclosed techniques detects both SWs and respiration events, along with the phase between them, and combines these with a haptic interface that delivers a haptic signal to the Parkinson’s patient when they fail to swallow at the proper time. By doing this over time, the embodiments herein can ‘train’ the Parkinson’s patient to swallow at the ideal time—i.e. the safe swallow interval—thereby improving their quality of life. [0083] Such a process can be driven by an algorithm 59 such as that shown in Fig.7. The algorithm 59 is typically coded using embedded computer code and operates on the microprocessor within the sensor. As shown in Fig.7, the algorithm 59 begins after the sensor is applied to the patient, as indicated by Fig.1 (step 60). The sensor lacks any ‘on/off’ button and recognizes when it is attached to the patient. It begins by PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 collecting high-resolution waveforms, typically sampled between 500-2,000 Hz, along the x, y, and z-axes (step 62). These waveforms are stored in memory on the sensor, and continuously converted into a time-dependent energy signal, e.g. E(t) as described above, using a mathematical formula like that shown below (step 64). ^^( ^^) ~ √ ^^( ^^)² + ^^( ^^)² + ^^( ^^)² [0084] Peaks (PN) in the SWs are then detected using a ‘beatpicking’ algorithm (step 66); such peaks look like those shown in Fig. 3B and described above. The beatpicking algorithm can take one of many different forms. For example, the microprocessor can deploy a version of a conventional algorithm used to detect peaks in ECG waveforms, such as the well-known Pan-Thompkins algorithm. Alternatively, the microprocessor can analyze the E(t) signal with a digital filter (such as a band-pass filter), derivatize the filtered signal, and then analyze the derivatized signal to determine zero-point crossings that indicate slope changes associated with peaks in the waveform. Still other techniques can be used to determine the peaks in the waveform corresponding to SWs. [0085] The ACC signal and/or E(t) can be further processed to determine the patient’s RR and, perhaps more importantly, respiratory waveform (step 67). Fig. 9B shows an example of such a waveform, which includes periods of both inspiration (i.e. the upslope of respiration-induced peaks, indicated by arrows 80a-c in the figure) and expiration (downslope of respiration-induced peaks, indicated by arrows 82a-c in the figure). Analysis of such a waveform and its features, along with the peaks PN determined using the beatpicker, determines if PN occurs during the appropriate time and is in phase with the low-to-medium tidal volumes during expiration, i.e. the safe swallow interval described above and shown in Fig. 5 (step 68). If it does, this indicates the patient is swallowing properly, and no haptic feedback is necessary. The algorithm returns to continuously measuring ACC waveforms along the internal accelerometer’s 3 axes (step 62). However, if PN falls outside the safe swallow interval—i.e. if swallowing occurs too soon or too late relative to the patient’s inspiration and expiration, or if no swallowing occurs at all—the sensor delivers to the patient a haptic signal in the form of PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 a light vibration or other type of haptic feedback. Once this is complete, the algorithm returns to continuously measuring ACC waveforms along the internal accelerometer’s 3 axes (step 62) and processing them as described above. [0086] As shown in Fig.8, the sensor 10 is configured to transmit information like that described above (e.g. processed numerical values and time-dependent waveforms) through a gateway device 72 and to the cloud 77. This allows, for example, a clinician to monitor the patient 14 remotely. For example, during a typical use case, the sensor 10 attaches to the patient’s SN and monitors the patient’s physiological response, e.g. their swallowing behavior along with pulmonary and cardiac signals. This information—i.e. both time-dependent waveforms and numerical values of HR, RR, and PN—are transmitted via Bluetooth®, as indicated by arrow 74, to the gateway device 72. The gateway device 72 is typically a mobile phone or tablet computer (e.g. one operating on Android or iOS operating systems) running a custom software application. Once the gateway device 72 and its custom software application receives information from the sensor, it transmits it to the cloud 77 using either a cellular or Wi-Fi transmitter, as indicated by arrow 75. And once in the cloud 77, the patient-generated information can be processed in a variety of ways. It can, for example, be: 1) stored in a database; 2) processed with various algorithms, e.g. algorithms based on machine learning or artificial intelligence, to estimate the patient’s physiological condition; 3) transmitted to a third-party software application, e.g. using a web services interface; and 4) transmitted to a hospital information system, such as an electronic medical record (EMR). A remote clinician can use this information to manage the patient, i.e. to: 1) collect information for a medical consultation; 2) prescribed medication; 3) initiate a haptic interface; and 4) simply observe the patient, e.g. for a clinical trial. [0087] Figs.9A, 9B, 10A, and 10B indicate, respectively, how the patient’s respiratory and cardiac signals are extracted from ACC waveforms and used to determine respiratory and cardiac parameters, such as waveforms and processed numerical values like RR and HR. Figs. 9A and 10A show raw, unfiltered ACC waveforms measured along the z-axis, which in this case corresponds to an axis pointing directly into the patient’s chest. The waveforms include cardiac components (shown as pairs of PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 sharp, high-frequency pulses, with two pulses corresponding to the S1 and S2 heart sounds corresponding to each heartbeat) and low-frequency undulations corresponding to heaving of the patient’s chest due to respiration, and more specifically to inspiration and expiration. [0088] When filtered with a bandpass filter, e.g. an infinite impulse response (herein “IIR”) bandpass filter with a low-frequency cutoff around 0.01 Hz and a high-frequency cutoff around 1 Hz, the ACC waveform shown in Fig.9A transforms into that shown in Fig.9B. The filter removes high-frequency noise and cardiac signals from the waveform, leaving only low-frequency undulations, driven by each of the patient’s breaths, corresponding to inspiration (as indicated by arrows 80a, 80b, and 80c) and expiration (arrows 82a, 82b, and 82c). These periods can be extracted from the filtered waveforms using well-known signal processing techniques to determine the safe swallow interval described above, particularly with reference to Figs.4 and 5. [0089] Fig. 10A, like Fig. 9A, shows the raw unfiltered ACC waveform. When filtered with an IIR bandpass filter with a low-frequency cutoff around 1 Hz and a high- frequency cutoff around 12 Hz, the ACC waveform shown in Fig. 10A transforms into that shown in Fig.10B. Here, the filter removes the respiratory signal shown in Fig.9B, which occurs at a relatively low frequency, leaving only high-frequency noise and a cardiac signal consisting of S1 and S2 heart sounds. These are indicated, respectively, by the black circles and squares. The S1 heart sound corresponds to the closing of the patient’s mitral and tricuspid valves; the S2 heart sound corresponds to closing of the aortic and pulmonary valves. These signals, for example, can be used to determine HR and other cardiac properties, such as systolic time intervals. Such timing intervals can be combined with physiological signals measured by other embodiments, such as ECG, impedance, and photoplethysmogram waveforms, to determine parameters called pulse arrival time (herein “PAT”) and pulse transit time (herein “PTT”). The inverse of PAT and PTT are known to correlate to changes in systolic (herein “SYS”) and diastolic (herein “DIA”) blood pressure. [0090] In related embodiments, the haptic interface can be coupled to vital signs and parameters not related to SWs, e.g. values of SYS and DIA determined by PAT, PTT, PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 and other methodologies. For example, the haptic interface could automatically be initiated if the patient’s blood pressure values trended beyond pre-determined limits that may be harmful to the patient. Such events could occur, for example, during periods of exercise, stress, etc. [0091] Patients suffering from Parkinson’s disease often fail to swallow regularly, a detrimental condition that can lead to negative outcomes. Thus, increased frequency of swallowing is generally considered to be a positive factor for patients suffering from this condition. To clinically test the concept of using a haptic interface to induce swallowing, a clinical study was performed using a body-worn sensor like that shown in Fig. 1, augmented to include four separate vibration motors and a Bluetooth® interface to a gateway device (like that shown in Fig. 8). The vibration motors were driven with a digital pulse width modulated (herein “PWM”) signal with amplitude shift key (herein “ASK”) modulation; this independently sets the vibration power of each of motor. The vibratory response (i.e. the haptic interface) is dictated by analysis of the phase of respiratory and swallow signals, as described above, performed by the gateway device in a manner consistent with that described above relative to Fig.7. [0092] Fig. 11A shows a time-dependent waveform—typical of that measured in this study— featuring well-defined, low-frequency signals due to respiration, and relative high-frequency signals due to SWs. Case 1, indicated by the dashed box 110a in the figure, corresponds to a SW that occurs during expiration in the safe swallow interval, as indicated in Figs.4 and 5. This indicates an ideal SW, and the corresponding haptic pattern involves all four motors operated three times in synchrony at 500 ms intervals, as indicated by the dashed box 110b Fig.11B, which shows vibrations detected by the accelerometer within the body-worn sensor. For training purposes, this would be viewed as a ‘positive’ response. [0093] Cases 2-5 in Fig. 11A correspond to non-ideal SWs and corresponding ‘negative’ responses. Here, the algorithm running on the gateway detects suboptimal respiratory-swallow phase patterns, shown by dashed boxes 112a, 114a, 116a, and activates all four vibrating motors at 250 ms intervals. This haptic interface, which indicates an improper swallow event to the patient, is shown by the dashed boxes 112b, PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 114b, 116b in Fig.11B. Over time, the patient will recognize these haptic signals as a negative response and subliminally adjust their swallowing pattern to one that is consistent with the safe swallow interval, which is marked by a positive response. In this way, the haptic interface can ‘train’ the patient to swallow in a healthier manner, thereby improving outcomes. [0094] Referring to Fig.12, a study with N = 20 subjects was conducted to prove this concept. Subjects were those suffering from Parkinson’s disease with a clinically diagnoses of dysphagia of any severity, as made by a speech language pathologist (herein “SLP”). During the study each subject wore a sensor like that shown in Fig.1, and underwent passive activity. SWs were monitored by the SLP (serving as the reference device) and the sensor (test device); the sensor independently monitored respiration, and used this to generate a haptic interface, as described above. More specifically, an algorithm operating on the sensor processed the phase of the swallow and respiration events to determine the safe swallow interval, as described above, and initiated haptic feedback when the phase of these events was misaligned. Subjects were measured with and without haptic feedback to estimate the efficacy of this approach for increasing SWs, a metric, as described above, that indicates improved outcomes for patients with Parkinson’s disease. [0095] Fig. 12 shows the results of this study, which indicates the haptic interface increases SWs from 0.7 swallows/minute in the group not receiving the haptic interface to 1.1 swallows/minute, for the group receiving the haptic interface. This represents an increase of 57% in swallowing frequency, a benefit attributed to the technique described herein. Similar benefits are expected for other patients with conditions that impact their swallowing, such as patients suffering from head and neck cancer, Alzheimer’s disease and other forms of dementia, Myasthenia Gravis, ALS, and related diseases. [0096] Referring to Figs. 13, 13A, and 13B, the sensor shown in Fig. 1 may take on other configurations, such as one where a first portion 122 of the sensor features a battery and electronic system (e.g. power management circuitry, vibratory motors for the haptic interface) and measurement systems for measuring physiological signals like HR and RR (e.g. a first accelerometer, electrode-containing ECG and/or impedance PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 circuitry). The first portion 122 connects to a second portion 124 that includes a second accelerometer for measuring SWs. The connection is made with a third portion 126 that includes electrical conductors. [0097] Such a spatially distributed system uses separate, decoupled sensors (i.e. motion-detecting accelerometers) to measure respiratory and SWs, thus simplifying analyses of these data to interpedently measure a respiratory waveforms and SWs and ultimately determine the safe swallow interval. When coupled with the haptic interface, as described above, this may improve the precision to which this parameter can be determined. [0098] Figs. 13A and 13B show, for example, how this sensor may be applied to a patient. In Fig.13A, the first portion 122 of the sensor is applied directly to the patient’s chest, a location where accurate measurement of RR is most likely to be made. As described above, this parameter can be measured with one or more different sensing modalities, e.g. an accelerometer, ECG, and/or impedance circuitry, the latter of which is described in more detail below. The third portion 126 is positioned proximal to the patient’s larynx to more accurately measure SWs. The decoupled and distributed nature of this configuration results in relatively high accuracy of RR and SWs; when coupled with the haptic interface, this increases the sensor’s impact on the patient, e.g. its ability to increase the frequency of SWs. [0099] Fig.13B shows the sensor 120 worn in yet another configuration on the patient. Here, the first portion (hidden by the patient’s shirt in the figure) is worn even lower on the patient’s chest; this location—directly above the patient’s heart and lungs—typically results in relatively accurate measurements of HR and RR. The second portion 124, which connects to the first portion through the third portion 126, is positioned directly on the patient’s suprasternal notch. As described above, this is an ideal location for measuring SW. [00100] Still other combinations of the first 122, second 124, and third 126 portions, as shown in Figs.13, 13A, and 13B, are within the scope of the claims set forth below. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [00101] In other embodiments, sensors directed at detecting other parameters, such as vital signs including HR, RR, pulse oximetry (herein “SpO2”), temperature, and SYS/DIA blood pressure, may include the haptic interface described herein. The haptic interface may be used to create a ‘feedback loop’ that drives the patient to modify an activity (e.g. motion, exercise, stress, sleeping in a certain position) when the vital signs fall outside a pre-determined range. Referring to Fig.14, for example, sensors containing the haptic interface may include a patch 152 or oximeter 154 worn, respectively, on the chest or finger of a patient 150. Here, the patch 152 measures both ECG and impedance waveforms that yield values of HR and RR. The oximeter measures SpO2 values along with HR and RR. Both sensors can additionally include temperature sensors to measure skin temperature. [00102] For the patch 152, single-use electrodes secure the sensor to the patient’s chest. The electrodes may include pairs of ‘sense’ and ‘drive’ electrodes to detect bioelectric signals that, after processing, yield the ECG and impedance waveforms as described above. For the impedance measurements, the pair of ‘drive’ electrodes are configured to inject high-frequency, low-amperage current into the patient’s chest. Current can be injected at multiple frequencies ranging from about 5-1000KHz, and typically has an amplitude of about 0.1-1.0 mA. The pair of sense electrodes measure bio-electric signals that, once processed, yield time-dependent ECG and impedance waveforms. When further processed such waveforms yield HR, RR, respiratory tidal volume, stroke volume, and cardiac output. [00103] The patch 152 may also include a reflective optical sensor that features an LED emitting red and infrared wavelengths. In embodiments, a circular array of photodetectors surround the LED. A thin, Kapton ^ film with embedded electrical traces surrounds the photodetectors and LED, and generates heat when a voltage is applied; this gently warms the skin to 41oC -42oC using a closed-loop system, thereby increasing perfusion and amplifying the corresponding optical waveforms and increasing the accuracy of the SpO2 measurement. [00104] The patch 152 may include a thermally conductive metal post that connects to a temperature sensor (not shown in the figure) and the patient’s skin, during a PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 measurement. With this, the patch 152 can measure skin temperature. It is powered by a rechargeable Li-ion battery that can be charged through a small-scale USB port, or alternatively with an embedded transformer that performs wireless charging. In still other embodiments, the patch 152 includes an acoustic sensor configured to measure S1 and S2 heart sounds. [00105] Referring to Figs. 15A, 15B, and 15C, in still other embodiments, an accelerometer-containing sensor 10 like that shown in Fig.1 (and shown again in Fig. 15A) is worn on different parts of the patient 12, such as their hand (Fig.15B) and upper arm (Fig. 15C). More specifically, in Fig. 15B, the sensor 10b is worn on the patient’s hand 12b. In this configuration, the haptic interface is initiated during a scratching event, and may be used to ‘train’ the patient to reduce scratching and response to other types of skin irritation. In Fig.15C, the sensor 10c is worn on the patient’s arm 12c, and the haptic interface may be used to reduce motion of the arm, or keep the patient from raising their arm above a certain level. [00106] In other embodiments, the sensor described herein could count physiological events that can be easily measured with an accelerometer, like coughing, sneezing, and aspiration, and then apply a haptic interface to the patient when these events exceed a predetermined level. [00107] In other embodiments, the sensors described herein can be used in combination with other equipment used in the hospital and home, such as a feeding tube, e.g. a feeding tube coupled with a neurostimulating device. For example, the sensor and its haptic interface can act in combination with the neurostimulating feeding tube to trigger swallowing at the optimal time. In other embodiments, the sensor and its haptic interface, when coupled to the feeding tube, could also allow for external manual modulation of the neurostimulation. For example, the sensor could include a button that, when pressed, triggers internal neurostimulation from the feeding tube. [00108] In other embodiments, the haptic interface can be timed to decrease the amount of drooling experienced by the patient. The body-worn sensor can also include a microphone which measures sounds emitted by the patient, and can be used to decrease the patient’s slurring or drive them to speak louder if their speech is too light. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [00109] Still further, those in the art having the benefit of this disclosure will appreciate that the physiological sensor may be implemented as a motion sensor, such as an accelerometer or one or more ECG leads; or a respiration sensor; or an acoustic sensor, such as a microphone sensor, as is described above. In embodiments in which the physiological sensor is implemented as a microphone sensor, the microphone sensor may be used to gather other acoustic signals such as sounds generated by the patient’s body by swallowing or breathing (i.e., through respiration). [00110] In a first embodiment, a sensor worn entirely on a patient’s body comprises a microphone sensor, a haptic interface, and a processing system. The microphone sensor is configured to measure acoustic signals generated by the patient’s body. The haptic interface is configured to generate a haptic response. The processing system is programmed to receive the acoustic signals from the microphone sensor and execute computer code that: processes the measured acoustic signals to detect swallowing, respiration, coughing, or a combination thereof; and controls the haptic interface to generate the haptic response responsive to the processing of the measured acoustic signals. [00111] In a second embodiment, in the sensor of the first embodiment, the measured acoustic signals are generated by the patient’s body through swallowing, respiration, coughing, or combinations thereof. [00112] In a third embodiment, in the sensor of the first embodiment, the haptic response is responsive to a predetermined parameter indicating a temporal point for the patient to swallow. [00113] In a fourth embodiment, the sensor of the first embodiment further comprises an accelerometer. [00114] In a fifth embodiment, in the sensor of the fourth embodiment, the processing system is programmed to process at least one time-dependent motion signal with a first algorithm to determine a time-dependent energy signal. [00115] In a sixth embodiment, in the sensor of the fifth embodiment: the first algorithm is configured to collectively processes time-dependent motion signals measured by the PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 accelerometer along the x, y, and z-axes to determine the time-dependent energy signal; and the first algorithm uses the following equation, or a mathematical variation thereof, to determine the time-dependent energy signal: ^^( ^^) ~ √ ^^( ^^)² + ^^( ^^)² + ^^( ^^)² [00116] where E(t) is the , y(t), and z(t) are the time- dependent motion signals measured by the accelerometer along, respectively, the x, y, and z-axes corresponding to the patient. [00117] In a seventh embodiment, in the sensor of the first embodiment, processing the acoustic signals includes applying a convolutional neural network to the acoustic signals. [00118] In an eighth embodiment, in the sensor of the first embodiment, the processing system is further programmed to process an amplitude of the acoustic signals. [00119] In a ninth embodiment, in the sensor of the first embodiment, the processing system is further programmed to determine a frequency profile of the acoustic signals. [00120] In a tenth embodiment, in the sensor of the ninth embodiment, the processing system is further programmed to determine an amplitude of a select frequency component within the frequency profile. [00121] In an eleventh embodiment, a method for assisting a patient with swallowing, comprises: measuring a plurality of acoustic signals generated by the patient’s body; processing the measured acoustic signals to detect swallowing, respiration, coughing, or a combination thereof, of the patient; and controlling the haptic interface to generate a haptic response responsive to the processing of the measure acoustic signals. [00122] In a twelfth embodiment, in the method of the eleventh embodiment, the measured acoustic signals are generated by the patient’s body through swallowing, respiration, coughing, or combinations thereof. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [00123] In a thirteenth embodiment, in the method of the eleventh embodiment, the haptic response is responsive to a predetermined parameter indicating a temporal point for the patient to swallow. [00124] In a fourteenth embodiment, the method of the eleventh embodiment further comprises measuring the patient’s movement. [00125] In a fifteenth embodiment, a wearable sensor comprises a first physiological sensor, a haptic interface, and a processing system. The first physiological sensor configured to acquire a first set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase. The haptic interface configured to generate a haptic response. The processing system programmed to receive the motion signals from the motion sensor and to: process the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; and control the haptic interface to generate the haptic response by collectively processing the first and second signals and a pre-determined parameter indicating an opportunity for the patient to swallow. [00126] In a sixteenth embodiment, in the wearable sensor of the fifteenth embodiment: the first physiological sensor is a motion sensor; the first set of physiological signals comprise time-dependent motion signals modulated by the patient’s swallowing and respiration; and the pre-determined parameter is a temporal point. [00127] In a seventeenth embodiment, in the wearable sensor of the fifteenth embodiment: the first physiological sensor is a respiration sensor; the first set of physiological signals comprises time-dependent electrical signals modulated by the patient’s respiration; and the pre-determined parameter is a temporal point. [00128] In an eighteenth embodiment, the wearable sensor of the fifteenth embodiment further comprises a second physiological sensor configured to acquire a second set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [00129] In a nineteenth embodiment, in the wearable sensor of the eighteenth embodiment: the second physiological sensor is a respiration sensor; and the second set of physiological signals comprises time-dependent electrical signals modulated by the patient’s respiration. [00130] In a twentieth embodiment, in the sensor of the fifteenth embodiment, the second signal is a time-dependent signal indicating the patient’s inspiration and expiration. [00131] In a twenty-first embodiment, in the sensor of the twentieth embodiment, the predetermined parameter indicates a temporal period when the patient should be expiring, and the processing system generates the haptic response when it determines that the swallowing event does not occur when the patient is expiring, the swallowing event occurs when the patient is inspiring, or the swallowing event occurs between when the patient is inspiring and expiring. [00132] In a twenty-second embodiment, in the wearable sensor of the fifteenth embodiment: the first physiological sensor is a microphone sensor; the first set of physiological signals comprises acoustic signals modulated by the patient’s speech volume; and the pre-determined parameter indicates a volume of the patient’s speech. [00133] In a twenty-third embodiment, in the wearable sensor of the fifteenth embodiment: the first physiological sensor is a microphone sensor; and the first set of physiological sensors comprise acoustic signals generated by the patient’s body by swallowing, respiration, or a combination thereof. [00134] In a twenty-fourth embodiment, a computer-implemented method, comprises: receiving a first set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase from a first physiological sensor, the first physiological sensor positioned on the patient’s suprasternal notch; processing the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; processing the first and second signals and a pre-determined parameter PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 indicating an opportunity for the patient to swallow; and generating a haptic response through a haptic interface, the haptic response to prompt the patient to swallow. [00135] In a twenty-fifth embodiment, in the computer-implemented method of the twenty-fourth embodiment, the first physiological sensor is a motion sensor, a respiration sensor, or a microphone sensor. [00136] In a twenty-sixth embodiment, the computer-implemented method of the twenty-fourth embodiment further comprises a second physiological sensor configured to acquire a second set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase. [00137] In a twenty-seventh embodiment, in the computer-implemented method of the twenty-sixth embodiment: the second physiological sensor is a respiration sensor; and the second set of physiological signals comprises time-dependent electrical signals modulated by the patient’s respiration. [00138] In a twenty-eighth embodiment, a system comprises a wearable sensor, an external gateway, and a computing system. The wearable sensor is configured to: acquire a first set of physiological signals from a patient, the first set of physiological signals being potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase; process the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; and generate a haptic response indicating an opportunity for the patient to swallow. The external gateway is programmed to wirelessly receive information transmitted from the wearable sensor. The computing system may be use to store or access the transmitted information. [00139] In a twenty-ninth embodiment, in the system of the twenty-eighth embodiment, the wearable sensor further comprises: a first physiological sensor configured to acquire the first set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase; a haptic interface configured to generate the haptic response; and the processing system is programmed to receive the motion signals from the motion sensor and to: process the first set of physiological signals to PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; and control the haptic interface to generate the haptic response by collectively processing the first and second signals and a pre-determined parameter indicating an opportunity for the patient to swallow. [00140] In a thirtieth embodiment, in the system of the twenty-ninth embodiment, the first physiological sensor is a motion sensor, a respiration sensor, or a microphone sensor. [00141] In a thirty-first embodiment, the system of the twenty-ninth embodiment further comprises a second physiological sensor programmed to acquire a second set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase. [00142] In a thirty-second embodiment, in the system of thirty-first embodiment: the second physiological sensor is a respiration sensor; and the second set of physiological signals comprises time-dependent electrical signals modulated by the patient’s respiration. [00143] In a thirty-third embodiment, in the sensor of the first embodiment, processing the measured acoustic signals yields a determination that a swallowing frequency exceeds a threshold parameter, and the haptic response is generated responsive to the determination. [00144] In a thirty-fourth embodiment, in the sensor of the first embodiment, the microphone sensor is a microphone. [00145] Unless a term is expressly defined herein using the phrase “herein”, or a similar sentence, there is no intent to limit the meaning of that term beyond its plain or ordinary meaning. To the extent that any term is referred to in this document in a manner consistent with a single meaning, that is done for sake of clarity only; it is not intended that such claim term be limited to that single meaning. Finally, unless a claim element is defined by reciting the word “means” and a function without the recital of any structure, it is not intended that the scope of any claim element be interpreted based on the application of 35 U.S.C. § 112(f). PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [00146] The several aspects of the wearable sensor disclosed herein are described as “configured to” perform some function. In some contexts, the phrase “configured to” means that design choices have been exercised to provide the ascribed capability. For example, for a wearable sensor to be configured to measure acoustic signals may mean that the wearable sensor includes a microphone sensor. In other contexts, the phrase “configured to” may indicate that a programmable electronic component has been programmed to perform the ascribed function. So, for another example, a wearable sensor including a processing system—or the processing system itself—may be configured to perform some function by appropriately programming the processing system. Those in the art having the benefit of this disclosure will be able to readily configure various aspects of the wearable sensor from the context provided herein. [00147] The expressions such as “include” and “may include” which may be used in the present disclosure denote the presence of the disclosed functions, operations, and constituent elements, and do not limit the presence of one or more additional functions, operations, and constituent elements. In the present disclosure, terms such as “include” and/or “have”, may be construed to denote a certain characteristic, number, operation, constituent element, component or a combination thereof, but should not be construed to exclude the existence of or a possibility of the addition of one or more other characteristics, numbers, operations, constituent elements, components or combinations thereof. [00148] As used herein, the article “a” is intended to have its ordinary meaning in the patent arts, namely “one or more.” Herein, the term “about” when applied to a value generally means within the tolerance range of the equipment used to produce the value, or in some examples, means plus or minus 10%, or plus or minus 5%, or plus or minus 1%, unless otherwise expressly specified. Further, herein the term “substantially” as used herein means a majority, or almost all, or all, or an amount with a range of about 51% to about 100%, for example. Moreover, examples herein are intended to be illustrative only and are presented for discussion purposes and not by way of limitation. [00149] As used herein, to "provide" an item means to have possession of and/or control over the item. This may include, for example, forming (or assembling) some or PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 all of the item from its constituent materials and/or, obtaining possession of and/or control over an already-formed item. [00150] Unless otherwise defined, all terms including technical and/or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present disclosure pertains. In addition, unless otherwise defined, all terms defined in generally used dictionaries may not be overly interpreted. In the following, details are set forth to provide a more thorough explanation of the embodiments. However, it will be apparent to those skilled in the art that embodiments may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form or in a schematic view rather than in detail in order to avoid obscuring the embodiments. In addition, features of the different embodiments described hereinafter may be combined with each other, unless specifically noted otherwise. For example, variations or modifications described with respect to one of the embodiments may also be applicable to other embodiments unless noted to the contrary. [00151] Further, equivalent or like elements or elements with equivalent or like functionality are denoted in the following description with equivalent or like reference numerals. As the same or functionally equivalent elements are given the same reference numbers in the figures, a repeated description for elements provided with the same reference numbers may be omitted. Hence, descriptions provided for elements having the same or like reference numbers are mutually exchangeable. [00152] It will be understood that when an element is referred to as being “connected” or “coupled” to another element, it can be directly connected or coupled to the other element or intervening elements may be present. In contrast, when an element is referred to as being “directly connected” or “directly coupled” to another element, there are no intervening elements present. Other words used to describe the relationship between elements should be interpreted in a like fashion (e.g., “between” versus “directly between,” “adjacent” versus “directly adjacent,” etc.). [00153] In the present disclosure, expressions including ordinal numbers, such as “first”, “second”, and/or the like, may modify various elements. However, such elements PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 are not limited by the above expressions. For example, the above expressions do not limit the sequence and/or importance of the elements. The above expressions are used merely for the purpose of distinguishing an element from the other elements. For example, a first box and a second box indicate different boxes, although both are boxes. For further example, a first element could be termed a second element, and similarly, a second element could also be termed a first element without departing from the scope of the present disclosure. [00154] A sensor refers to a component which converts a physical quantity to be measured to an electric signal, for example, a current signal or a voltage signal. The physical quantity may for example comprise electromagnetic radiation (e.g., photons of infrared or visible light), a magnetic field, an electric field, a pressure, a force, a temperature, a current, or a voltage, but is not limited thereto. [00155] Use of the phrases “capable of,” “capable to,” “operable to,” or “configured to” in one or more embodiments, refers to some apparatus, logic, hardware, and/or element designed in such a way to enable the use of the apparatus, logic, hardware, and/or element in a specified manner. Use of the phrase “exceed” in one or more embodiments, indicates that a measured value could be higher than a pre-determined threshold (e.g., an upper threshold), or lower than a pre-determined threshold (e.g., a lower threshold). When a pre-determined threshold range (defined by an upper threshold and a lower threshold) is used, the use of the phrase “exceed” in one or more embodiments could also indicate a measured value is outside the pre-determined threshold range (e.g., higher than the upper threshold or lower than the lower threshold). The subject matter of the present disclosure is provided as examples of apparatus, systems, methods, circuits, and programs for performing the features described in the present disclosure. However, further features or variations are contemplated in addition to the features described above. It is contemplated that the implementation of the components and functions of the present disclosure can be done with any newly arising technology that may replace any of the above-implemented technologies. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 [00156] The detailed description is made with reference to the accompanying drawings and is provided to assist in a comprehensive understanding of various example embodiments of the present disclosure. Changes may be made in the function and arrangement of elements discussed without departing from the spirit and scope of the disclosure. Various embodiments may omit, substitute, or add various procedures or components as appropriate. For instance, features described with respect to certain embodiments may be combined in other embodiments. In addition, descriptions of well- known functions and constructions may be omitted for clarity and conciseness. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the examples described herein can be made without departing from the spirit and scope of the present disclosure. [00157] Various modifications to the disclosure will therefore be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the present disclosure. Throughout the present disclosure the terms “example,” “examples,” or “exemplary” indicate examples or instances and do not imply or require any preference for the noted examples. Thus, the present disclosure is not to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed.

Claims

PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 CLAIMS What is claimed is: 1. A sensor worn entirely on a patient’s body, the sensor comprising: a microphone sensor configured to measure acoustic signals generated by the patient’s body; a haptic interface configured to generate a haptic response; and a processing system programmed to receive the acoustic signals from the microphone sensor and execute computer code that: processes the measured acoustic signals to detect swallowing, respiration, coughing, or a combination thereof; and controls the haptic interface to generate the haptic response responsive to the processing of the measured acoustic signals. 2. The sensor of claim 1, wherein the measured acoustic signals are generated by the patient’s body through swallowing, respiration, coughing, or combinations thereof. 3. The sensor of claim 1, wherein the haptic response is responsive to a predetermined parameter indicating a temporal point for the patient to swallow. 4. The sensor of claim 1, further comprising an accelerometer. 5. The sensor of claim 4, wherein the processing system is programmed to process at least one time-dependent motion signal with a first algorithm to determine a time- dependent energy signal. 6. The sensor of claim 5, wherein: the first algorithm is configured to collectively processes time-dependent motion signals measured by the accelerometer along the x, y, and z-axes to determine the time-dependent energy signal; and PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 the first algorithm uses the following equation, or a mathematical variation thereof, to determine the time-dependent energy signal: ^^( ^^) ~ ^√ ^^( ^^)² + ^^( ^^)² + ^^( ^^)² where E(t) is (t), y(t), and z(t) are the time- dependent the accelerometer along, respectively, the x, y, and z-axes corresponding to the patient. 7. The sensor of claim 1, wherein processing the acoustic signals includes applying a convolutional neural network to the acoustic signals. 8. The sensor of claim 1, wherein the processing system is further programmed to process an amplitude of the acoustic signals. 9. The sensor of claim 1, wherein the processing system is further programmed to determine a frequency profile of the acoustic signals. 10. The sensor of claim 9, wherein the processing system is further programmed to determine an amplitude of a select frequency component within the frequency profile. 11. A method for assisting a patient with swallowing, comprising: measuring a plurality of acoustic signals generated by the patient’s body; processing the measured acoustic signals to detect swallowing, respiration, coughing, or a combination thereof, of the patient; and controlling the haptic interface to generate a haptic response responsive to the processing of the measure acoustic signals. 12. The method of claim 11, the measured acoustic signals are generated by the patient’s body through swallowing, respiration, coughing, or combinations thereof. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 13. The method of claim 11, wherein the haptic response is responsive to a predetermined parameter indicating a temporal point for the patient to swallow. 14. The method of claim 11, further comprising measuring the patient’s movement. 15. A wearable sensor, comprising: a first physiological sensor configured to acquire a first set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase; a haptic interface configured to generate a haptic response; and a processing system programmed to receive motion signals from a motion sensor and to: process the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; and control the haptic interface to generate the haptic response by collectively processing the first and second signals and a pre-determined parameter indicating an opportunity for the patient to swallow. 16. The wearable sensor of claim 15, wherein: the first physiological sensor is a motion sensor; the first set of physiological signals comprise time-dependent motion signals modulated by the patient’s swallowing and respiration; and the pre-determined parameter is a temporal point. 17. The wearable sensor of claim 15, wherein: the first physiological sensor is a respiration sensor; the first set of physiological signals comprises time-dependent signals modulated by the patient’s respiration; and the pre-determined parameter is a temporal point. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 18. The wearable sensor of claim 15, further comprising a second physiological sensor configured to acquire a second set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase. 19. The wearable sensor of claim 18, wherein: the second physiological sensor is a respiration sensor; and the second set of physiological signals comprises time-dependent electrical signals modulated by the patient’s respiration. 20. The sensor of claim 15, wherein the second signal is a time-dependent signal indicating the patient’s inspiration and expiration. 21. The sensor of claim 20, wherein the predetermined parameter indicates a temporal period when the patient should be expiring, and the processing system generates the haptic response when it determines that the swallowing event does not occur when the patient is expiring, the swallowing event occurs when the patient is inspiring, or the swallowing event occurs between when the patient is inspiring and expiring. 22. The wearable sensor of claim 15, wherein: the first physiological sensor is a microphone sensor; the first set of physiological signals comprises acoustic signals modulated by the patient’s speech volume; and the pre-determined parameter indicates a volume of the patient’s speech. 23. The wearable sensor of claim 15, wherein: the first physiological sensor is a microphone sensor; and the first set of physiological sensors comprise acoustic signals generated by the patient’s body by swallowing, respiration, or a combination thereof. 24. A computer-implemented method, comprising: PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 receiving a first set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase from a first physiological sensor, the first physiological sensor positioned on the patient’s suprasternal notch; processing the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; processing the first and second signals and a pre-determined parameter indicating an opportunity for the patient to swallow; and generating a haptic response through a haptic interface, the haptic response to prompt the patient to swallow. 25. The computer-implemented method of claim 24, wherein the first physiological sensor is a motion sensor, a respiration sensor, or a microphone sensor. 26. The computer-implemented method of claim 24, further comprising a second physiological sensor configured to acquire a second set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase. 27. The computer-implemented method of claim 26, wherein: the second physiological sensor is a respiration sensor; and the second set of physiological signals comprises time-dependent electrical signals modulated by the patient’s respiration. 28 A system, comprising: a wearable sensor configured to: acquire a first set of physiological signals from a patient, the first set of physiological signals being potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase; PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 process the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; and generate a haptic response indicating an opportunity for the patient to swallow; an external gateway programmed to wirelessly receive information transmitted from the wearable sensor; and a computing system in which the transmitted information may be stored or through which the transmitted information may be accessed. 29. The system of claim 28, wherein the wearable sensor further comprises: a first physiological sensor configured to acquire the first set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase; a haptic interface configured to generate the haptic response; and a processing system programmed to receive the motion signals from the motion sensor and to: process the first set of physiological signals to determine a first signal related to a presence or absence of a swallowing event and a second signal related to the patient’s respiration; and control the haptic interface to generate the haptic response by collectively processing the first and second signals and a pre-determined parameter indicating an opportunity for the patient to swallow. 30. The system of claim 29, wherein the first physiological sensor is a motion sensor, a respiration sensor, or a microphone sensor. 31. The system of claim 29, further comprising a second physiological sensor programmed to acquire a second set of physiological signals potentially indicative of a patient’s swallowing events relative to the patient’s respiratory phase. PATENT ATTY DOCKET NO. SIBEL-006PCT Customer No.143770 32. The system of claim 31, wherein: the second physiological sensor is a respiration sensor; and the second set of physiological signals comprises time-dependent electrical signals modulated by the patient’s respiration. 33. The sensor of claim 1, wherein: processing the measured acoustic signals yields a determination that a swallowing frequency exceeds a threshold parameter; and the haptic response is generated responsive to the determination. 34. The sensor of claim 1, wherein the microphone sensor is a microphone.