Evaluation of Patients' Levels of Walking Independence Using Inertial Sensors and Neural Networks in an Acute-Care Hospital.

This study aimed to evaluate walking independence in acute-care hospital patients using neural networks based on acceleration and angular velocity from two walking tests. Forty patients underwent the 10-m walk test and the Timed Up-and-Go test at normal speed, with or without a cane. Physiotherapists divided the patients into two groups: 24 patients who were monitored or independent while walking with a cane or without aids in the ward, and 16 patients who were not. To classify these groups, the Transformer model analyzes the left gait cycle data from eight inertial sensors. The accuracy using all the sensor data was 0.836. When sensor data from the right ankle, right wrist, and left wrist were excluded, the accuracy decreased the most. When analyzing the data from these three sensors alone, the accuracy was 0.795. Further reducing the number of sensors to only the right ankle and wrist resulted in an accuracy of 0.736. This study demonstrates the potential of a neural network-based analysis of inertial sensor data for clinically assessing a patient's level of walking independence.

Effects of the walking independence on lower extremity and trunk muscle activity during straight-leg raising following incomplete cervical cord injury.

The purpose of this study was to compare the acceleration and surface electromyography (EMG) of the lower extremity and trunk muscles during straight-leg raising (SLR) in patients with incomplete cervical cord injury according to their levels of walking independence. Twenty-four patients were measured acceleration and EMG during SLR held for 10 s. Data were analyzed separately for the dominant and nondominant sides and compared between the nonindependent (NI) and independent (ID) groups based on their levels of walking independence. Frequency analysis of the EMG showed that the high-frequency (HF) band of the contralateral biceps femoris (BF) in the ID group and bands below the medium-frequency (MF) of the BF and the HF and MF bands of the rectus abdominis in the NI group were significantly higher during dominant and nondominant SLR. During the nondominant SLR, the low-frequency band of the internal oblique and the MF band of the external oblique were significantly higher in the NI group. The ID group mobilized muscle fiber type 2 of the BF, whereas the NI group mobilized type 1 of the BF and types 2 and 1 of the trunk muscles to stabilize the pelvis. This result was more pronounced during the nondominant SLR.

Ultraflexible Wireless Imager Integrated with Organic Circuits for Broadband Infrared Thermal Analysis.

Flexible imagers are currently under intensive development as versatile optical sensor arrays, designed to capture images of surfaces and internals, irrespective of their shape. A significant challenge in developing flexible imagers is extending their detection capabilities to encompass a broad spectrum of infrared light, particularly terahertz (THz) light at room temperature. This advancement is crucial for thermal and biochemical applications. In this study, a flexible infrared imager is designed using uncooled carbon nanotube (CNT) sensors and organic circuits. The CNT sensors, fabricated on ultrathin 2.4 µm substrates, demonstrate enhanced sensitivity across a wide infrared range, spanning from near-infrared to THz wavelengths. Moreover, they retain their characteristics under bending and crumpling. The design incorporates light-shielded organic transistors and circuits, functioning reliably under light irradiation, and amplifies THz detection signals by a factor of 10. The integration of both CNT sensors and shielded organic transistors into an 8 × 8 active-sensor matrix within the imager enables sequential infrared imaging and nondestructive assessment for heat sources and in-liquid chemicals through wireless communication systems. The proposed imager, offering unique functionality, shows promise for applications in biochemical analysis and soft robotics.

Broadband Photodetectors and Imagers in Stretchable Electronics Packaging.

The integration of flexible electronics with optics can help realize a powerful tool that facilitates the creation of a smart society wherein internal evaluations can be easily performed nondestructively from the surface of various objects that is used or encountered in daily lives. Here, organic-material-based stretchable optical sensors and imagers that possess both bending capability and rubber-like elasticity are reviewed. The latest trends in nondestructive evaluation equipment that enable simple on-site evaluations of health conditions and abnormalities are discussed without subjecting the targeted living bodies and various objects to mechanical stress. Real-time performance under real-life conditions is becoming increasingly important for creating smart societies interwoven with optical technologies. In particular, the terahertz (THz)-wave region offers a substance- and state-specific fingerprint spectrum that enables instantaneous analyses. However, to make THz sensors accessible, the following issues must be addressed: broadband and high-sensitivity at room temperature, stretchability to follow the surface movements of targets, and digital transformation compatibility. The materials, electronics packaging, and remote imaging systems used to overcome these issues are discussed in detail. Ultimately, stretchable optical sensors and imagers with highly sensitive and broadband THz sensors can facilitate the multifaceted on-site evaluation of solids, liquids, and gases.

A high prevalence of myeloid malignancies in progeria with Werner syndrome is associated with p53 insufficiency.

Werner syndrome (WS) is a progeroid syndrome caused by mutations in the WRN gene, which encodes the RecQ type DNA helicase for the unwinding of unusual DNA structures and is implicated in DNA replication, DNA repair, and telomere maintenance. patients with WS are prone to develop malignant neoplasms, including hematological malignancies. However, the pathogenesis of WS-associated hematological malignancies remains uncharacterized. Here we investigated the somatic gene mutations in WS-associated myelodysplastic syndrome/acute myeloid leukemia (MDS/AML). Whole-exome sequencing (WES) of 4 patients with WS with MDS/AML revealed that all patients had somatic mutations in TP53 but no other recurrent mutations in MDS/AML. TP53 mutations were identified at low allele frequencies at more than one year before the MDS/AML stage. All 4 patients had complex chromosomal abnormalities including those that involved TP53. Targeted sequencing of nine patients with WS without apparent blood abnormalities did not detect recurrent mutations in MDS/AML except for a PPM1D mutation. These results suggest that patients with WS are apt to acquire TP53 mutations and/or chromosomal abnormalities involving TP53, rather than other MDS/AML-related mutations. TP53 mutations are frequently associated with prior exposure to chemotherapy; however, all four patients with WS with TP53 mutations/deletions had not received any prior chemotherapy, suggesting a pathogenic link between WRN mutations and p53 insufficiency. These results indicate that WS hematopoietic stem cells with WRN insufficiency acquire competitive fitness by inactivating p53, which may cause complex chromosomal abnormalities and the subsequent development of myeloid malignancies. These findings promote our understanding of the pathogenesis of myeloid malignancies associated with progeria.

Effectiveness of the heartbeat interval error and compensation method on heart rate variability analysis.

The purpose of this study is to evaluate the effectiveness of heartbeat error and compensation methods on heart rate variability (HRV) with mobile and wearable sensor devices. The HRV analysis extracts multiple indices related to the heart and autonomic nervous system from beat-to-beat intervals. These HRV analysis indices are affected by the heartbeat interval mismatch, which is caused by sampling error from measurement hardware and inherent errors from the state of human body. Although the sampling rate reduction is a common method to reduce power consumption on wearable devices, it degrades the accuracy of the heartbeat interval. Furthermore, wearable devices often use photoplethysmography (PPG) instead of electrocardiogram (ECG) to measure heart rate. However, there are inherent errors between PPG and ECG, because the PPG is affected by blood pressure fluctuations, vascular stiffness, and body movements. This paper evaluates the impact of these errors on HRV analysis using dataset including both ECG and PPG from 28 subjects. The evaluation results showed that the error compensation method improved the accuracy of HRV analysis in time domain, frequency domain and non-linear analysis. Furthermore, the error compensation by the algorithm was found to be effective for both PPG and ECG.

Analysis of nocturnal desaturation waveforms using algorithms in patients with idiopathic pulmonary fibrosis.

PURPOSE: Sleep-disordered breathing is recognized as a comorbidity in patients with idiopathic pulmonary fibrosis (IPF). Among them, nocturnal hypoxemia has been reported to be associated with poor prognosis and disease progression. We developed a diagnostic algorithm to classify nocturnal desaturation from percutaneous oxygen saturation (SpO2) waveform patterns: sustained pattern, periodic pattern, and intermittent pattern. We then investigated the prevalence of nocturnal desaturation and the association between the waveform patterns of nocturnal desaturation and clinical findings of patients with IPF. METHODS: We prospectively enrolled patients with IPF from seven general hospitals between April 2017 and March 2020 and measured nocturnal SpO2 and nasal airflow by using a home sleep apnea test. An algorithm was used to classify the types of nocturnal desaturation. We evaluated the association between sleep or clinical parameters and each waveform pattern of nocturnal desaturation. RESULTS: Among 60 patients (47 men) who met the eligibility criteria, there were 3 cases with the sustained pattern, 49 cases with the periodic pattern, and 41 cases with the intermittent pattern. Lowest SpO2 during sleep and total sleep time spent with SpO2 < 90% were associated with the sustained pattern, and apnea-hypopnea index was associated with the intermittent pattern. CONCLUSION: We demonstrated the prevalence of each waveform and association between each waveform and sleep parameters in patients with IPF. This classification algorithm may be useful to predict the degree of hypoxemia or the complication of obstructive sleep apnea.

Successful allogeneic bone marrow transplantation after massive gastrointestinal bleeding in a patient with myelodysplastic syndrome associated with intestinal Behçet-like disease.

A 45-year-old woman was diagnosed with myelodysplastic syndrome (MDS) with trisomy 8 and Behçet-like disease (BLD) with multiple colorectal ulcers. Nonspecific inflammatory cells were infiltrated in the intestinal mucosa, whereas fluorescence in situ hybridization (FISH) analysis revealed only sporadic trisomy 8-positive cells. She presented massive lower gastrointestinal bleeding early after bone marrow transplantation but achieved long-term remission of both MDS and BLD. This is the first report of massive gastrointestinal bleeding after transplantation for MDS with BLD. Based on FISH analysis, dysregulation of systemic inflammation may be involved in BLD rather than direct invasion by trisomy 8-positive MDS clones.

Prospective Study of Nocturnal Desaturation in Patients Receiving Home Oxygen Therapy.

Objective Nocturnal desaturation is common in patients with chronic respiratory disease and often worsens the prognosis. Therefore, it should be diagnosed accurately and appropriately treated. The aim of this study was to clarify the diversity of nocturnal desaturation. Methods We prospectively enrolled 58 outpatients diagnosed with chronic respiratory disease receiving home oxygen therapy and measured nocturnal SpO2 using a portable oximeter. We classified nocturnal desaturation (3% decrease in SpO2 from baseline) into three patterns: periodic pattern (desaturation duration of <655 seconds), sustained pattern (desaturation duration of ≥655 seconds), and intermittent pattern (desaturation and recovery of SpO2 repeated with a cycle of several minutes). Results Nocturnal hypoxemia (SpO2≤88% for more than 5 minutes) was found in 23.8% of patients. The percentage of patients with chronic obstructive pulmonary disease (COPD) was significantly higher in the nocturnal hypoxemia group than in the non-hypoxemia group (80% vs. 40.6%, p=0.03). Desaturation with a periodic pattern was found in 81% of patients, desaturation with a sustained pattern was found in 40.5% of patients, and desaturation with an intermittent pattern was found in 59.5% of patients. In patients with COPD, desaturation with a periodic pattern was found in 85.7%, desaturation with a sustained pattern was found in 47.6%, and desaturation with an intermittent pattern was found in 57.1%. Conclusion The SpO2 waveform of nocturnal hypoxemia was able to be classified into three patterns. Suitable treatment for each pattern might improve the prognosis of these patients.

Characteristics of the nocturnal desaturation waveform pattern of SpO2 in COPD patients: an observational study.

BACKGROUND: Nocturnal desaturation is common in patients with chronic obstructive pulmonary disease (COPD) and impacts disease exacerbation and prognosis. In our previous study, we developed a diagnostic algorithm to classify nocturnal desaturation from SpO2 waveform patterns based on data from patients receiving home oxygen therapy. In this study, we aimed to investigate nocturnal desaturation in patients with COPD based on SpO2 waveform patterns and the associations between the waveforms and clinical data. METHODS: We investigated patients diagnosed with COPD and measured SpO2 and nasal airflow with a type 4 portable long-term recordable pulse oximeter. Then, we classified the SpO2 waveforms with the algorithm and compared the clinical data. RESULTS: One hundred fifty-three patients (136 male and 17 female) were analysed. One hundred twenty-eight of the 153 (83.7%) patients had nocturnal desaturation, with an intermittent pattern (70.6%), sustained pattern (13.1%) and periodic pattern (68.0%). Intriguingly, desaturation with an intermittent pattern was associated with the apnoea-hypopnea index obtained with the portable monitor, and desaturation with a sustained pattern was associated with the cumulative percentage of time at a SpO2 below 90%. CONCLUSIONS: We found that nocturnal desaturation was frequently observed in patients with COPD and could be classified into 3 types of waveform patterns.

A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor.

Objective evaluations of cough frequency are considered important for assessing the clinical state of patients with respiratory diseases. However, cough monitors with audio recordings are rarely used in clinical settings. Issues regarding privacy and background noise with audio recordings are barriers to the wide use of these monitors; to solve these problems, we developed a novel automatic cough frequency monitoring system combining a triaxial accelerator and a stretchable strain sensor. Eleven healthy adult volunteers and 10 adult patients with cough were enrolled. The participants wore two devices for 30 min for the cough measurements. An accelerator was attached to the epigastric region, and a stretchable strain sensor was worn around their neck. When the subjects coughed, these devices displayed specific waveforms. The data from all the participants were categorized into a training dataset and a test dataset. Using a variational autoencoder, a machine learning algorithm with deep learning, the components of the test dataset were automatically judged as being a "cough unit" or "non-cough unit". The sensitivity and specificity in detecting coughs were 92% and 96%, respectively. Our cough monitoring system has the potential to be widely used in clinical settings without any concerns regarding privacy or background noise.

Wireless Monitoring Using a Stretchable and Transparent Sensor Sheet Containing Metal Nanowires.

Mechanically and visually imperceptible sensor sheets integrated with lightweight wireless loggers are employed in ultimate flexible hybrid electronics (FHE) to reduce vital stress/nervousness and monitor natural biosignal responses. The key technologies and applications for conceptual sensor system fabrication are reported, as exemplified by the use of a stretchable sensor sheet completely conforming to an individual's body surface to realize a low-noise wireless monitoring system (<1 µV) that can be attached to the human forehead for recording electroencephalograms. The above system can discriminate between Alzheimer's disease and the healthy state, thus offering a rapid in-home brain diagnosis possibility. Moreover, the introduction of metal nanowires to improve the transparency of the biocompatible sensor sheet allows one to wirelessly acquire electrocorticograms of nonhuman primates and simultaneously offers optogenetic stimulation such as toward-the-brain-machine interface under free movement. Also discussed are effective methods of improving electrical reliability, biocompatibility, miniaturization, etc., for metal nanowire based tracks and exploring the use of an organic amplifier as an important component to realize a flexible active probe with a high signal-to-noise ratio. Overall, ultimate FHE technologies are demonstrated to achieve efficient closed-loop systems for healthcare management, medical diagnostics, and preclinical studies in neuroscience and neuroengineering.

Low-Noise Photoplethysmography Sensor Using Correlated Double Sampling for Heartbeat Interval Acquisition.

This study designs a low-power photoplethysmography (PPG) sensor based on the error compensation method for heartbeat interval acquisition. To perform heartbeat monitoring in daily life, it is necessary to obtain long-term and accurate heartbeat interval data with low power consumption, because of the limited size and battery capacity of the PPG sensor. Effective reduction in the power consumption of the sensor requires the duty-cycled LEDs and lowering pulse repetition frequency (PRF), i.e., decreasing the sampling rate. However, these methods reduce the accuracy of the heartbeat interval measurement because of signal-to-noise ratio (SNR) degradation and sampling errors. We propose an algorithm for heartbeat interval error compensation and incorporate a low-noise readout circuit to improve SNR. The readout circuit uses current integration to achieve low duty-cycle LED driving. A correlated double sampling (CDS) is introduced to minimize the random noise arising from the switching operation of the integration circuit. An error compensation method based on the PPG waveform similarity is also introduced using the autocorrelation and linear interpolation. The measurement results obtained from nine subjects show that a total current consumption of 28.2 µA is achieved with a 20-Hz PRF and 0.3% LED duty cycle. The proposed design effectively reduces the mean absolute error (MAE) of the heartbeat interval to an average of 6.2 ms.

Classification Algorithm for Nocturnal Hypoxemia Using Nocturnal Pulse Oximetry.

This paper describes an automatic classification algorithm for nocturnal hypoxemia in patients receiving home oxygen therapy (HOT). Nocturnal hypoxemia is a well-known complication in patients with chronic respiratory disease, and the number of patients receiving HOT has increased in recent years. Many studies have reported that 40% of patients receiving HOT have sleep-related oxygen desaturation. To deal with this situation, a nocturnal pulse oximetry is used to measure oxygen saturation (SpO2) and control the flow rate of highly concentrated oxygen. However, in some cases, the flow rate is not controlled properly and the same flow rate is adopted both during the day and night. There are several types of nocturnal hypoxemia, and it is difficult to classify these types only according to a subjective assessment of a medical doctor. Furthermore, it is difficult to continuously monitor the measurement results of pulse oximetry, although a flexible treatment depending on the state of hypoxemia is desired. To overcome these difficulties, an automatic classification method for SpO2 measured by the nocturnal pulse oximetry is proposed in this paper. The proposed method uses the time domain waveform and the frequency characteristics of SpO2. The classification performance of the method is evaluated by using 48 measured SpO2 values from patients receiving the HOT. The classification results are validated with decisions of ten chest physicians.

A 5-ms Error, 22-µA Photoplethysmography Sensor using Current Integration Circuit and Correlated Double Sampling.

This paper presents a low-power Photoplethysmography (PPG) sensing method. The PPG is commonly used in recent wearable devices to detect cardiovascular information including heartbeat. The heartbeat is useful for physical activity and stress monitoring. However, the PPG circuit consumes large power because it consists of LED and photodiode. To reduce its power consumption without accuracy degradation, a cooperative design of circuits and algorithms is proposed in this work. A straightforward way to reduce the power is intermittent driving of LED, but there is a disadvantage that the signal is contaminated by a noise while circuit switching. To overcome this problem, we introduce correlated double sampling (CDS) method, which samples an integration circuit output twice with short intervals after the LED turns on and uses the difference of these voltage. Furthermore, an up-conversion method using linear interpolation, and an error correction using autocorrelation are introduced. The proposed PPG sensor, which consists of the LED, the photodiode, the current integration circuit, a CMOS switch, an A/D converter, and an MCU, is prototyped. It is evaluated by actual measurement with 22-year-old subject. The measurement results show that 22-µA total current consumption is achieved with 5-ms mean absolute error.

Estimating metabolic equivalents for activities in daily life using acceleration and heart rate in wearable devices.

BACKGROUND: Herein, an algorithm that can be used in wearable health monitoring devices to estimate metabolic equivalents (METs) based on physical activity intensity data, particularly for certain activities in daily life that make MET estimation difficult. RESULTS: Energy expenditure data were obtained from 42 volunteers using indirect calorimetry, triaxial accelerations and heart rates. The proposed algorithm used the percentage of heart rate reserve (%HRR) and the acceleration signal from the wearable device to divide the data into a middle-intensity group and a high-intensity group (HIG). The two groups were defined in terms of estimated METs. Evaluation results revealed that the classification accuracy for both groups was higher than 91%. To further facilitate MET estimation, five multiple-regression models using different features were evaluated via leave-one-out cross-validation. Using this approach, all models showed significant improvements in mean absolute percentage error (MAPE) of METs in the HIG, which included stair ascent, and the maximum reduction in MAPE for HIG was 24% compared to the previous model (HJA-750), which demonstrated a 70.7% improvement ratio. The most suitable model for our purpose that utilized heart rate and filtered synthetic acceleration was selected and its estimation error trend was confirmed. CONCLUSION: For HIG, the MAPE recalculated by the most suitable model was 10.5%. The improvement ratio was 71.6% as compared to the previous model (HJA-750C). This result was almost identical to that obtained from leave-one-out cross-validation. This proposed algorithm revealed an improvement in estimation accuracy for activities in daily life; in particular, the results included estimated values associated with stair ascent, which has been a difficult activity to evaluate so far.

[MALT lymphoma accompanied by elevated serum IgM levels mimicking Waldenström's macroglobulinemia].

A 60-year-old man with chronic hepatitis C was referred to our hospital with significantly elevated total protein and serum IgM (9,500 mg/dl) levels identified via a routine checkup. Blood examination revealed increased serum IgM-monoclonal protein and serum-soluble IL-2 receptor (sIL2R) levels. Computed tomography and fluorodeoxyglucose positron emission tomography revealed pulmonary masses, abnormal soft tissue masses surrounding the bilateral kidneys, and thickened mucous membrane of the bladder with high fluorodeoxyglucose uptake. Pathological examination of the pulmonary mass revealed infiltration of medium-sized lymphocytes and plasma cells. Immunohistochemical analysis revealed tumor cells positive for CD138 and IgM, with a low positive rate of Ki-67 expression. Notably, the tumor cell-surrounding lymphocytes were positive for CD20. Although the patient was initially regarded as having Waldenström's macroglobulinemia owing to the significantly increased serum IgM levels, based on positive IgH-MALT1 translocation and negative MYD88 L265P mutation findings, he was further diagnosed with extranodal marginal zone lymphoma of mucosa-associated lymphoid tissue (MALT lymphoma). Complete remission was achieved following six cycles of rituximab + CHOP therapy. This study data suggest that analysis of the MYD88 L265P mutation in tumor cells is suitable for accurately diagnosing hematopoietic malignancies with increased IgM monoclonal protein.

A swallowable sensing device platform with wireless power feeding and chemical reaction actuator.

This paper presents a swallowable sensor device that can be ingested orally, later passing to the stomach, where the device can indwell for long periods. Using wireless communication, it can be egested at any time after it is triggered. This device can indwell using a silicone balloon in the gastrointestinal tract. A chemical reaction inflates the balloon inside the stomach. Then it is deflated to egest the sensor device using an actuator with electrolysis of water. Energy for the actuator with electrolysis can be fed wirelessly. Near field communication and a flexible antenna are used for power feeding and wireless data communication. Because of the flexible balloon and the flexible antenna, the device size can be minimized without performance degradation.