US-20260123850-A1 - ASSESSMENT OF LUNG CAPACITY, RESPIRATORY FUNCTION, ABDOMINAL STRENGTH AND/OR THORACIC STRENGTH OR IMPAIRMENT

Abstract

A diagnostic device configured to assess respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of a subject, the diagnostic device comprising: a processor; a microphone; and a memory storing computer-readable instructions that, when executed by the processor, cause the diagnostic device to: prompt the subject to perform a diagnostic task of making a long “aaah” sound for a predetermined duration; receive audio data associated with the diagnostic task via the microphone; extract, from the audio data, digital biomarker data; and apply an analytical model to the extracted digital biomarker data, the analytical model configured to generate an output indicative of the respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of the subject

Inventors

• Doris BERCHTOLD
• Foteini ORFANIOTOU
• Thanneer Malai PERUMAL
• Anja Kaja RIES

Assignees

• HOFFMANN-LA ROCHE INC.

Dates

Publication Date

20260507

Application Date

20231006

Priority Date

20221007

Claims (20)

1. 1 . A diagnostic device configured to assess respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of a subject, the diagnostic device comprising: a processor; a microphone; and a memory storing computer-readable instructions that, when executed by the processor, cause the diagnostic device to: prompt the subject to perform a diagnostic task of making a long “aaah” sound for a predetermined duration; receive audio data associated with the diagnostic task via the microphone; extract, from the audio data, digital biomarker data; and apply an analytical model to the extracted digital biomarker data, the analytical model configured to generate an output indicative of the respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of the subject.
2. 2 . A diagnostic device according to claim 1 , wherein: the audio data comprises a plurality of segments; and extracting the digital biomarker data comprises applying a first algorithm to the audio data, the first algorithm configured to classify the segments of the audio data into active speech segments and background noise segments.
3. 3 . A diagnostic device according to claim 2 , wherein: classifying the segments of the audio data into active speech segments and background noise segments comprises generating timestamps indicating the beginning and end times of each respective active speech segment and background noise segment.
4. 4 . A diagnostic device according to claim 2 wherein: each active speech segment comprises a plurality of sub-segments; and extracting the digital biomarker data comprises applying a second algorithm to the active speech segments of the audio data, the second algorithm configured to classify the sub-segments into voiced speech sub-segments and non-voiced speech sub-segments.
5. 5 . A diagnostic device according to claim 4 , wherein: classifying the sub-segments of the active speech segments of the audio data into voiced speech segments and non-voiced speech segments comprises generating timestamps indicating the beginning and end times of each respective voiced speech sub-segment and non-voiced speech sub-segment.
6. 6 . A diagnostic device according to claim 5 , wherein: the digital biomarker data comprises a total duration of voiced speech sub-segments within the predetermined duration of the diagnostic task.
7. 7 . A diagnostic device according to claim 5 wherein: the digital biomarker data comprises a total number of voiced speech sub-segments in the active speech segments of the audio data.
8. 8 . A diagnostic device according to claim 5 , wherein: the digital biomarker data comprises one or more of the duration of the longest voice speech sub-segment and the shortest voiced speech sub-segment in the active speech segments of the audio data.
9. 9 . A diagnostic device according to claim 5 , wherein: the digital biomarker data comprises a total duration of non-voiced speech sub-segments within the predetermined duration of the diagnostic task.
10. 10 . A diagnostic device according to claim 5 , wherein: the digital biomarker data comprises one or more of the duration of the longest non-voiced speech sub-segment and the shortest non-voiced speech sub-segment in the active speech segments of the audio data.
11. 11 . A diagnostic device according to claim 1 , wherein: the computer-readable instructions, when executed by the processor, further cause the device to prompt the subject to place the device at a pre-determined distance from the subject.
12. 12 . A diagnostic device according to claim 1 , wherein: the computer-readable instructions, when executed by the processor, further cause the device to prompt the subject to place the device in a pre-determined position.
13. 13 . A diagnostic device according to claim 1 , wherein: the computer-readable instructions, when executed by the processor, further cause the device to: receive, via the microphone, noise data; calculate, from the noise data, a background noise; and use the background noise to apply a correction to the audio data.
14. 14 . A diagnostic device according to claim 1 , wherein: the audio data is received over a period of 30 seconds.
15. 15 . A diagnostic device according to claim 1 , wherein: the device is a smartphone.
16. 16 . A diagnostic device according to claim 1 wherein the computer-readable instructions, when executed by the at least one processor, cause the diagnostic device to apply a clinical interpretation model to the output indicative of the respiratory function, wherein the clinical interpretation model outputs an indication of the presence or absence of a muscular disability.
17. 17 . A diagnostic device according to claim 16 , wherein the clinical interpretation model is configured to compare the output indicative of the respiratory function to a predetermined value, and, based on the comparison, to output an indication of the presence or absence of the muscular disability.
18. 18 . A diagnostic device according to claim 17 , wherein the clinical interpretation model is configured to: determine whether the output indicative of the respiratory function is greater than a predetermined threshold; and, if it is determined that the output indicative of the respiratory function is greater than the predetermined threshold, to output an indication of the presence of a muscular disability; and, if it is determined that the output indicative of the respiratory function is less than or equal to the predetermined threshold, to output an indication of the absence of the muscular disability.
19. 19 . A diagnostic device according to claim 17 , wherein the clinical interpretation model is configured to: determine whether the output indicative of the respiratory function is less than a predetermined threshold; and, if it is determined that the output indicative of the respiratory function is less than the predetermined threshold, to output an indication of the presence of a muscular disability; and, if it is determined that the output indicative of the respiratory function is greater than or equal to the predetermined threshold, to output an indication of the absence of the muscular disability.
20. 20 . A computer-implemented method of configured to assess respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of a subject, the method comprising: prompting the subject to perform a diagnostic task of making a long “aaah” sound for a predetermined duration; receiving audio data associated with the diagnostic task via the microphone; extracting, from the audio data, digital biomarker data; and applying an analytical model to the extracted digital biomarker data, the analytical model configured to generate an output indicative of the respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of the subject.

Description

TECHNICAL FIELD OF THE INVENTION The present invention relates to diagnostic device and computer-implemented methods configured to assess respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of a subject. BACKGROUND TO THE INVENTION People living with spinal muscular atrophy (SMA) report difficulty speaking loudly (e.g. to make themselves heard in a noisy environment), and may experience shortness of breath while speaking. Moreover, the Scientific Advisory Working Group (SAWG) recommended that combining measurements from speech and respiration assessments could help detect worsening of bulbar function that might foreshadow critical events (such as aspirations). In addition, since people with spinal muscular atrophy report difficulty speaking loudly, it is hypothesized that the sound pressure level1 of speech might be a further outcome measure. I This is often incorrectly referred to as “loudness”—loudness is a psychoacoustic term that refers to the subjective perception of sound pressure, and is affected by factors such the frequency-dependent sensitivity of human hearing, and masking effects that are used in audio compression schemes such as MP3. Unless these effects of human hearing are being modeled, the term level should be used. It is desirable to measure the respiratory function, lung capacity, and abdominal/thoracic/strength/impairment, since this can help to track the status or progression of various conditions, such as SMA. The present inventors have devised a scheme to do so. SUMMARY OF THE INVENTION The present invention provides a diagnostic device and computer-implemented methods of assessing respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of a subject of a subject. The outputs may be useful in assessing bulbar function of a subject, and to track the status or progression of conditions affecting bulbar function, such as (but not exclusively) SMA. More specifically, a first aspect of the present invention provides a diagnostic device configured to assess respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of a subject, the diagnostic device comprising: a processor; a microphone; and a memory storing computer-readable instructions that, when executed by the processor, cause the diagnostic device to: prompt the subject to perform a diagnostic task of making a long “aaah” sound for a predetermined duration; receive audio data associated with the diagnostic task via the microphone; extract, from the audio data, digital biomarker data; and apply an analytical model to the extracted digital biomarker data, the analytical model configured to generate an output indicative of the respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of the subject. By measuring respiratory function using a diagnostic device according to the first aspect of the present invention, it may be possible to track, effectively, the progress of various muscular disabilities such as SMA in a subject by active testing of the subject. In particular, the computer-readable instructions, when executed by the processor, may be further configured to cause the diagnostic device to map the output a bulbar function assessment grade indicative of the bulbar function of the subject. As is described in detail later in this application, the diagnostic device according to the first aspect of the present invention may use the output indicative of the respiratory function and/or the bulbar function assessment grade to indicate and/or track the presence or progression of a muscular disability, such as SMA, in a subject or user. In preferred implementations, the device is or comprises a smartphone. This is advantageous because smartphones are possessed by virtually everyone nowadays. By implementing a computer-implemented process such as the one described on a smartphone, a user need not attend e.g. a hospital or other clinical setting in order for the respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of a subject to be measured. Other kinds of diagnostic device may be used, e.g. a tablet, a laptop computer, a desktop computer, or the like. Alternatively, the diagnostic device may be a dedicated diagnostic device for assessing respiratory function, lung capacity, abdominal strength and/or thoracic strength or impairments of a subject. It is generally preferable to extract the digital biomarker data only from portions of the recorded audio data in which the user is actually vocalizing. However, the recorded audio data may include e.g. background noise before the subject begins performing the diagnostic task, and after they have completed it. More specifically, the audio data may comprise a plurality of segments, and extracting the digital biomarker data may comprise applying a first algorithm to the audio data, the first algorithm